Source Code for Module test_suite.system_tests.relax_disp

   1  ############################################################################### 
   2  #                                                                             # 
   3  # Copyright (C) 2006-2015 Edward d'Auvergne                                   # 
   4  # Copyright (C) 2009 Sebastien Morin                                          # 
   5  # Copyright (C) 2013-2014 Troels E. Linnet                                    # 
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   7  # This file is part of the program relax (http://www.nmr-relax.com).          # 
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  23   
  24  # Python module imports. 
  25  from os import F_OK, access, getcwd, path, sep 
  26  from numpy import array, asarray, exp, median, inf, linspace, log, save, std, sum, zeros 
  27  from minfx.generic import generic_minimise 
  28  from random import gauss 
  29  import re, math 
  30  from sys import version_info 
  31  from tempfile import mkdtemp, NamedTemporaryFile 
  32   
  33   
  34  # relax module imports. 
  35  from auto_analyses import relax_disp 
  36  from auto_analyses.relax_disp_repeat_cpmg import DIC_KEY_FORMAT, Relax_disp_rep 
  37  from data_store import Relax_data_store; ds = Relax_data_store() 
  38  import dep_check 
  39  from lib.dispersion.variables import EXP_TYPE_CPMG_DQ, EXP_TYPE_CPMG_MQ, EXP_TYPE_CPMG_PROTON_MQ, EXP_TYPE_CPMG_PROTON_SQ, EXP_TYPE_CPMG_SQ, EXP_TYPE_CPMG_ZQ, EXP_TYPE_LIST, EXP_TYPE_R1RHO, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99, MODEL_LIST_ANALYTIC_CPMG, MODEL_LIST_FULL, MODEL_LIST_NUMERIC_CPMG, MODEL_LM63, MODEL_M61, MODEL_M61B, MODEL_MP05, MODEL_NOREX, MODEL_NS_CPMG_2SITE_3D_FULL, MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_R1RHO_2SITE, MODEL_NS_R1RHO_3SITE, MODEL_NS_R1RHO_3SITE_LINEAR, MODEL_PARAMS, MODEL_R2EFF, MODEL_TP02, MODEL_TAP03 
  40  from lib.errors import RelaxError 
  41  from lib.io import extract_data, get_file_path, open_read_file 
  42  from lib.spectrum.nmrpipe import show_apod_extract, show_apod_rmsd, show_apod_rmsd_dir_to_files, show_apod_rmsd_to_file 
  43  from pipe_control.mol_res_spin import display_spin, generate_spin_string, return_spin, spin_loop 
  44  from pipe_control.minimise import assemble_scaling_matrix 
  45  from pipe_control.pipes import display 
  46  from specific_analyses.relax_disp.checks import check_missing_r1 
  47  from specific_analyses.relax_disp.estimate_r2eff import estimate_r2eff 
  48  from specific_analyses.relax_disp.data import average_intensity, check_intensity_errors, generate_r20_key, get_curve_type, has_exponential_exp_type, has_r1rho_exp_type, loop_exp_frq, loop_exp_frq_offset_point, loop_exp_frq_offset_point_time, loop_time, return_grace_file_name_ini, return_param_key_from_data, spin_ids_to_containers 
  49  from specific_analyses.relax_disp.data import INTERPOLATE_DISP, INTERPOLATE_OFFSET, X_AXIS_DISP, X_AXIS_W_EFF, X_AXIS_THETA, Y_AXIS_R2_R1RHO, Y_AXIS_R2_EFF 
  50  from specific_analyses.relax_disp.model import models_info, nesting_param 
  51  from specific_analyses.relax_disp.parameters import linear_constraints 
  52  from status import Status; status = Status() 
  53  from target_functions.relax_fit_wrapper import Relax_fit_opt 
  54  from test_suite.system_tests.base_classes import SystemTestCase 
  55   
  56   
  57 -class Relax_disp(SystemTestCase): 
  58      """Class for testing various aspects specific to relaxation dispersion curve-fitting.""" 
  59   
  60 -    def __init__(self, methodName='runTest'): 
  61          """Skip certain tests if the C modules are non-functional. 
  62   
  63          @keyword methodName:    The name of the test. 
  64          @type methodName:       str 
  65          """ 
  66   
  67          # Execute the base class method. 
  68          super(Relax_disp, self).__init__(methodName) 
  69   
  70          # Tests to skip. 
  71          blacklist = [ 
  72              'test_m61b_data_to_m61b' 
  73          ] 
  74          if methodName in blacklist: 
  75              status.skipped_tests.append([methodName, None, self._skip_type]) 
  76   
  77          # Missing module. 
  78          if not dep_check.C_module_exp_fn: 
  79              # The list of tests to skip. 
  80              to_skip = [ 
  81                  "test_bug_atul_srivastava", 
  82                  "test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp", 
  83                  "test_bug_9999_slow_r1rho_r2eff_error_with_mc", 
  84                  "test_estimate_r2eff_err", 
  85                  "test_estimate_r2eff_err_auto", 
  86                  "test_estimate_r2eff_err_methods", 
  87                  "test_finite_value", 
  88                  "test_exp_fit", 
  89                  "test_m61_exp_data_to_m61", 
  90                  "test_r1rho_kjaergaard_auto", 
  91                  "test_r1rho_kjaergaard_auto_check_graphs", 
  92                  "test_r1rho_kjaergaard_man", 
  93                  "test_r1rho_kjaergaard_missing_r1", 
  94                  "test_value_write_calc_rotating_frame_params_auto_analysis" 
  95              ] 
  96   
  97              # Store in the status object. 
  98              if methodName in to_skip: 
  99                  status.skipped_tests.append([methodName, 'Relax curve-fitting C module', self._skip_type]) 
 100   
 101          # If not scipy.optimize.leastsq. 
 102          if not dep_check.scipy_module: 
 103              # The list of tests to skip. 
 104              to_skip = [ 
 105                  "test_estimate_r2eff_err_methods" 
 106              ] 
 107   
 108              # Store in the status object. 
 109              if methodName in to_skip: 
 110                  status.skipped_tests.append([methodName, 'scipy.optimize.leastsq module', self._skip_type]) 
 111   
 112          # If not NMRPipe showApod program in PATH. 
 113          if not dep_check.showApod_software: 
 114              # The list of tests to skip. 
 115              to_skip = [ 
 116                  "test_show_apod_extract", 
 117                  "test_show_apod_rmsd", 
 118                  "test_show_apod_rmsd_to_file", 
 119                  "test_show_apod_rmsd_dir_to_files" 
 120              ] 
 121   
 122              # Store in the status object. 
 123              if methodName in to_skip: 
 124                  status.skipped_tests.append([methodName, 'NMRPipe showApod program', self._skip_type]) 
 125   
 126          # If not matplotlib module 
 127          if not dep_check.matplotlib_module: 
 128              # The list of tests to skip. 
 129              to_skip = [ 
 130                  "test_repeat_cpmg" 
 131              ] 
 132   
 133              # Store in the status object. 
 134              if methodName in to_skip: 
 135                  status.skipped_tests.append([methodName, 'matplotlib module', self._skip_type]) 
 136   
 137   
 138 -    def setUp(self): 
 139          """Set up for all the functional tests.""" 
 140   
 141          # Create the data pipe. 
 142          self.interpreter.pipe.create('relax_disp', 'relax_disp') 
 143   
 144          # Create a temporary directory for dumping files. 
 145          ds.tmpdir = mkdtemp() 
 146          self.tmpdir = ds.tmpdir 
 147   
 148   
 149 -    def setup_bug_22146_unpacking_r2a_r2b_cluster(self, folder=None, model_analyse=None, places = 7): 
 150          """Setup data for the catch of U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered full dispersion models. 
 151   
 152          @keyword folder:            The name of the folder for the test data. 
 153          @type folder:               str 
 154          @keyword model_analyse:     The name of the model which will be tested. 
 155          @type model_analyse:        str 
 156          """ 
 157   
 158          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
 159   
 160          # Data. 
 161          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22146_unpacking_r2a_r2b_cluster'+sep+folder 
 162   
 163          ## Experiments 
 164          # Exp 1 
 165          sfrq_1 = 500.0*1E6 
 166          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
 167          time_T2_1 = 0.05 
 168          ncycs_1 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 50] 
 169          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 170          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 171          r2eff_errs_1 = [0.0] * len(ncycs_1) 
 172          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
 173   
 174          sfrq_2 = 600.0*1E6 
 175          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
 176          time_T2_2 = 0.06 
 177          ncycs_2 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 60] 
 178          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 179          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 180          r2eff_errs_2 = [0.0] * len(ncycs_2) 
 181          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
 182   
 183          sfrq_3 = 700.0*1E6 
 184          r20_key_3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_3) 
 185          time_T2_3 = 0.07 
 186          ncycs_3 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 50, 70] 
 187          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 188          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 189          r2eff_errs_3 = [0.0] * len(ncycs_3) 
 190          exp_3 = [sfrq_3, time_T2_3, ncycs_3, r2eff_errs_3] 
 191   
 192          # Collect all exps 
 193          exps = [exp_1, exp_2, exp_3] 
 194   
 195          R20 = [5.1, 5.2, 5.3, 10.1, 10.2, 10.3, 6.1, 6.2, 6.3, 11.1, 11.2, 11.3, 7.1, 7.2, 7.3, 12.1, 12.2, 12.3, 8.1, 8.2, 8.3, 13.1, 13.2, 13.3] 
 196          dw_arr = [1.0, 2.0, 3.0, 4.0] 
 197          pA_arr = [0.9] 
 198          kex_arr = [1000.] 
 199   
 200          spins = [ 
 201                  ['Ala', 1, 'N', {'r2a': {r20_key_1: R20[0], r20_key_2: R20[1], r20_key_3: R20[2]}, 'r2b': {r20_key_1: R20[3], r20_key_2: R20[4], r20_key_3: R20[5]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[0]}], 
 202                  ['Ala', 2, 'N', {'r2a': {r20_key_1: R20[6], r20_key_2: R20[7], r20_key_3: R20[8]}, 'r2b': {r20_key_1: R20[9], r20_key_2: R20[10], r20_key_3: R20[11]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[1]}], 
 203                  ['Ala', 3, 'N', {'r2a': {r20_key_1: R20[12], r20_key_2: R20[13], r20_key_3: R20[14]}, 'r2b': {r20_key_1: R20[15], r20_key_2: R20[16], r20_key_3: R20[17]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[2]}], 
 204                  ['Ala', 4, 'N', {'r2a': {r20_key_1: R20[18], r20_key_2: R20[19], r20_key_3: R20[20]}, 'r2b': {r20_key_1: R20[21], r20_key_2: R20[22], r20_key_3: R20[23]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[3]}], 
 205                  ] 
 206   
 207          # Create the data pipe. 
 208          pipe_name = 'base pipe' 
 209          pipe_type = 'relax_disp' 
 210          pipe_bundle = 'relax_disp' 
 211          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type, bundle = pipe_bundle) 
 212   
 213          # Generate the sequence. 
 214          for res_name, res_num, spin_name, params in spins: 
 215              self.interpreter.spin.create(res_name=res_name, res_num=res_num, spin_name=spin_name) 
 216   
 217          # Set isotope 
 218          self.interpreter.spin.isotope('15N', spin_id='@N') 
 219   
 220          # Now loop over the experiments, to set the variables in relax. 
 221          exp_ids = [] 
 222          for exp_i in exps: 
 223              sfrq, time_T2, ncycs, r2eff_errs = exp_i 
 224              exp_id = 'CPMG_%3.1f' % (sfrq/1E6) 
 225              exp_ids.append(exp_id) 
 226   
 227              ids = [] 
 228              for ncyc in ncycs: 
 229                  nu_cpmg = ncyc / time_T2 
 230                  cur_id = '%s_%.1f' % (exp_id, nu_cpmg) 
 231                  ids.append(cur_id) 
 232   
 233                  # Set the spectrometer frequency. 
 234                  self.interpreter.spectrometer.frequency(id=cur_id, frq=sfrq) 
 235   
 236                  # Set the experiment type. 
 237                  self.interpreter.relax_disp.exp_type(spectrum_id=cur_id, exp_type=EXP_TYPE_CPMG_SQ) 
 238   
 239                  # Set the relaxation dispersion CPMG constant time delay T (in s). 
 240                  self.interpreter.relax_disp.relax_time(spectrum_id=cur_id, time=time_T2) 
 241   
 242                  # Set the relaxation dispersion CPMG frequencies. 
 243                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=cur_id, cpmg_frq=nu_cpmg) 
 244   
 245          print("\n\nThe experiment IDs are %s." % cdp.spectrum_ids) 
 246   
 247          ### Now do fitting. 
 248          # Change pipe. 
 249   
 250          pipe_name_MODEL = "%s_%s"%(pipe_name, model_analyse) 
 251          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_MODEL, bundle_to = pipe_bundle) 
 252          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
 253   
 254          # Now read data in. 
 255          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
 256              exp_id = exp_ids[mi] 
 257              exp_i = exps[mi] 
 258              sfrq, time_T2, ncycs, r2eff_errs = exp_i 
 259   
 260              # Then loop over the spins. 
 261              for res_name, res_num, spin_name, params in spins: 
 262                  cur_spin_id = ":%i@%s"%(res_num, spin_name) 
 263   
 264                  # Define file name 
 265                  file_name = "%s%s.txt" % (exp_id, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 
 266   
 267                  # Read in the R2eff file to put into spin structure. 
 268                  self.interpreter.relax_disp.r2eff_read_spin(id=exp_id, spin_id=cur_spin_id, file=file_name, dir=data_path, disp_point_col=1, data_col=2, error_col=3) 
 269   
 270          # Then select model. 
 271          self.interpreter.relax_disp.select_model(model=model_analyse) 
 272   
 273          # Then cluster 
 274          self.interpreter.relax_disp.cluster('model_cluster', ":1-100") 
 275   
 276          # Grid search 
 277          low_arr = R20 + dw_arr + pA_arr + kex_arr 
 278          self.interpreter.minimise.grid_search(lower=low_arr, upper=low_arr, inc=1, constraints=True, verbosity=1) 
 279   
 280          # Then loop over the defined spins and read the parameters. 
 281          for i in range(len(spins)): 
 282              res_name, res_num, spin_name, params = spins[i] 
 283              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
 284              cur_spin = return_spin(cur_spin_id) 
 285   
 286              for mo_param in cur_spin.params: 
 287                  print(mo_param) 
 288                  # The R2 is a dictionary, depending on spectrometer frequency. 
 289                  if isinstance(getattr(cur_spin, mo_param), dict): 
 290                      for key, val in list(getattr(cur_spin, mo_param).items()): 
 291                          should_be = params[mo_param][key] 
 292                          print(cur_spin.model, res_name, cur_spin_id, mo_param, key, float(val), should_be) 
 293                          self.assertAlmostEqual(val, should_be) 
 294                  else: 
 295                      should_be = float(params[mo_param]) 
 296                      val = getattr(cur_spin, mo_param) 
 297                      print(cur_spin.model, res_name, cur_spin_id, mo_param, val, should_be) 
 298                      self.assertAlmostEqual(val, should_be) 
 299   
 300              # Test chi2. 
 301              # At this point the chi-squared value at the solution should be zero, as the relaxation data was created with the same parameter values. 
 302              self.assertAlmostEqual(cur_spin.chi2, 0.0, places = places) 
 303   
 304   
 305 -    def setup_r1rho_kjaergaard(self, cluster_ids=[], read_R1=True): 
 306          """Set up the data for the test_r1rho_kjaergaard_*() system tests.""" 
 307   
 308          # The path to the data files. 
 309          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
 310   
 311          # Set pipe name, bundle and type. 
 312          ds.pipe_name = 'base pipe' 
 313          ds.pipe_bundle = 'relax_disp' 
 314          ds.pipe_type = 'relax_disp' 
 315   
 316          # Create the data pipe. 
 317          self.interpreter.pipe.create(pipe_name=ds.pipe_name, bundle=ds.pipe_bundle, pipe_type=ds.pipe_type) 
 318   
 319          # Read the spins. 
 320          self.interpreter.spectrum.read_spins(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 
 321   
 322          # Name the isotope for field strength scaling. 
 323          self.interpreter.spin.isotope(isotope='15N') 
 324   
 325          # Set number of experiments to be used. 
 326          NR_exp = 70 
 327   
 328          # Load the experiments settings file. 
 329          expfile = open(data_path+sep+'exp_parameters_sort.txt', 'r') 
 330          expfileslines = expfile.readlines()[:NR_exp] 
 331          expfile.close() 
 332   
 333          # In MHz 
 334          yOBS = 81.050 
 335          # In ppm 
 336          yCAR = 118.078 
 337          centerPPM_N15 = yCAR 
 338   
 339          ## Read the chemical shift data. 
 340          self.interpreter.chemical_shift.read(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 
 341   
 342          # The lock power to field, has been found in an calibration experiment. 
 343          spin_lock_field_strengths_Hz = {'35': 431.0, '39': 651.2, '41': 800.5, '43': 984.0, '46': 1341.11, '48': 1648.5} 
 344   
 345          # Apply spectra settings. 
 346          # Count settings 
 347          j = 0 
 348          for i in range(len(expfileslines)): 
 349              line = expfileslines[i] 
 350              if line[0] == "#": 
 351                  continue 
 352              else: 
 353                  # DIRN I deltadof2 dpwr2slock ncyc trim ss sfrq 
 354                  DIRN = line.split()[0] 
 355                  I = int(line.split()[1]) 
 356                  deltadof2 = line.split()[2] 
 357                  dpwr2slock = line.split()[3] 
 358                  ncyc = int(line.split()[4]) 
 359                  trim = float(line.split()[5]) 
 360                  ss = int(line.split()[6]) 
 361                  set_sfrq = float(line.split()[7]) 
 362                  apod_rmsd = float(line.split()[8]) 
 363                  spin_lock_field_strength = spin_lock_field_strengths_Hz[dpwr2slock] 
 364   
 365                  # Calculate spin_lock time 
 366                  time_sl = 2*ncyc*trim 
 367   
 368                  # Define file name for peak list. 
 369                  FNAME = "%s_%s_%s_%s_max_standard.ser"%(I, deltadof2, dpwr2slock, ncyc) 
 370                  sp_id = "%s_%s_%s_%s"%(I, deltadof2, dpwr2slock, ncyc) 
 371   
 372                  # Load the peak intensities. 
 373                  self.interpreter.spectrum.read_intensities(file=FNAME, dir=data_path+sep+'peak_lists', spectrum_id=sp_id, int_method='height') 
 374   
 375                  # Set the peak intensity errors, as defined as the baseplane RMSD. 
 376                  self.interpreter.spectrum.baseplane_rmsd(error=apod_rmsd, spectrum_id=sp_id) 
 377   
 378                  # Set the relaxation dispersion experiment type. 
 379                  self.interpreter.relax_disp.exp_type(spectrum_id=sp_id, exp_type='R1rho') 
 380   
 381                  # Set The spin-lock field strength, nu1, in Hz 
 382                  self.interpreter.relax_disp.spin_lock_field(spectrum_id=sp_id, field=spin_lock_field_strength) 
 383   
 384                  # Calculating the spin-lock offset in ppm, from offsets values provided in Hz. 
 385                  frq_N15_Hz = yOBS * 1E6 
 386                  offset_ppm_N15 = float(deltadof2) / frq_N15_Hz * 1E6 
 387                  omega_rf_ppm = centerPPM_N15 + offset_ppm_N15 
 388   
 389                  # Set The spin-lock offset, omega_rf, in ppm. 
 390                  self.interpreter.relax_disp.spin_lock_offset(spectrum_id=sp_id, offset=omega_rf_ppm) 
 391   
 392                  # Set the relaxation times (in s). 
 393                  self.interpreter.relax_disp.relax_time(spectrum_id=sp_id, time=time_sl) 
 394   
 395                  # Set the spectrometer frequency. 
 396                  self.interpreter.spectrometer.frequency(id=sp_id, frq=set_sfrq, units='MHz') 
 397   
 398                  # Add to counter 
 399                  j += 1 
 400   
 401   
 402          print("Testing the number of settings") 
 403          print("Number of settings iterations is: %s. Number of cdp.exp_type is: %s"%(i, len(cdp.exp_type))) 
 404          self.assertEqual(70, len(expfileslines)) 
 405          self.assertEqual(69, j) 
 406          self.assertEqual(69, len(cdp.exp_type)) 
 407   
 408          # Cluster spins 
 409          for curspin in cluster_ids: 
 410              print("Adding spin %s to cluster"%curspin) 
 411              self.interpreter.relax_disp.cluster('model_cluster', curspin) 
 412   
 413          # De-select for analysis those spins who have not been clustered 
 414          for free_spin in cdp.clustering['free spins']: 
 415              print("Deselecting free spin %s"%free_spin) 
 416              self.interpreter.deselect.spin(spin_id=free_spin, change_all=False) 
 417   
 418   
 419          #Paper         reference values 
 420          #              Resi   Resn         R1_rad_s   R1err_rad_s   R2_rad_s   R2err_rad_s   kEX_rad_s      kEXerr_rad_s  phi_rad2_s2     phierr_rad2_s2    phi_ppm2         phierr_ppm2 
 421          # Scaling rad2_s2 to ppm2: scaling_rad2_s2 = frequency_to_ppm(frq=1/(2*pi), B0=cdp.spectrometer_frq_list[0], isotope='15N')**2 = 3.85167990165e-06 
 422          ds.ref = dict() 
 423          ds.ref[':13@N'] = [13,   'L13N-HN',   1.32394,   0.14687,      8.16007,   1.01237,      13193.82986,   2307.09152,   58703.06446,    22413.09854,      0.2261054135,    0.0863280812] 
 424          ds.ref[':15@N'] = [15,   'R15N-HN',   1.34428,   0.14056,      7.83256,   0.67559,      13193.82986,   2307.09152,   28688.33492,    13480.72253,      0.110498283,     0.051923428] 
 425          ds.ref[':16@N'] = [16,   'T16N-HN',   1.71514,   0.13651,      17.44216,  0.98583,      13193.82986,   2307.09152,   57356.77617,    21892.44205,      0.220919942,     0.084322679] 
 426          ds.ref[':25@N'] = [25,   'Q25N-HN',   1.82412,   0.15809,      9.09447,   2.09215,      13193.82986,   2307.09152,   143111.13431,   49535.80302,      0.5512182797,    0.1907960569] 
 427          ds.ref[':26@N'] = [26,   'Q26N-HN',   1.45746,   0.14127,      10.22801,  0.67116,      13193.82986,   2307.09152,   28187.06876,    13359.01615,      0.1085675662,    0.051454654] 
 428          ds.ref[':28@N'] = [28,   'Q28N-HN',   1.48095,   0.14231,      10.33552,  0.691,        13193.82986,   2307.09152,   30088.0686,     13920.25654,      0.1158896091,    0.0536163723] 
 429          ds.ref[':39@N'] = [39,   'L39N-HN',   1.46094,   0.14514,      8.02194,   0.84649,      13193.82986,   2307.09152,   44130.18538,    18104.55064,      0.1699753481,    0.0697329338] 
 430          ds.ref[':40@N'] = [40,   'M40N-HN',   1.21381,   0.14035,      12.19112,  0.81418,      13193.82986,   2307.09152,   41834.90493,    17319.92156,      0.1611346625,    0.0667107938] 
 431          ds.ref[':41@N'] = [41,   'A41N-HN',   1.29296,   0.14286,      9.29941,   0.66246,      13193.82986,   2307.09152,   26694.8921,     13080.66782,      0.1028201794,    0.0503825453] 
 432          ds.ref[':43@N'] = [43,   'F43N-HN',   1.33626,   0.14352,      12.73816,  1.17386,      13193.82986,   2307.09152,   70347.63797,    26648.30524,      0.2709565833,    0.1026407417] 
 433          ds.ref[':44@N'] = [44,   'I44N-HN',   1.28487,   0.1462,       12.70158,  1.52079,      13193.82986,   2307.09152,   95616.20461,    35307.79817,      0.3682830136,    0.1359943366] 
 434          ds.ref[':45@N'] = [45,   'K45N-HN',   1.59227,   0.14591,      9.54457,   0.95596,      13193.82986,   2307.09152,   53849.7826,     21009.89973,      0.2074121253,    0.0809234085] 
 435          ds.ref[':49@N'] = [49,   'A49N-HN',   1.38521,   0.14148,      4.44842,   0.88647,      13193.82986,   2307.09152,   40686.65286,    18501.20774,      0.1567119631,    0.07126073] 
 436          ds.ref[':52@N'] = [52,   'V52N-HN',   1.57531,   0.15042,      6.51945,   1.43418,      13193.82986,   2307.09152,   93499.92172,    33233.23039,      0.3601317693,    0.1280037656] 
 437          ds.ref[':53@N'] = [53,   'A53N-HN',   1.27214,   0.13823,      4.0705,    0.85485,      13193.82986,   2307.09152,   34856.18636,    17505.02393,      0.1342548725,    0.0674237488] 
 438   
 439          ds.guess = dict() 
 440          ds.guess[':13@N'] = [13,   'L13N-HN',   1.32394,   0.14687,      8.16007,   1.01237,      13193.82986,   2307.09152,   58703.06446,    22413.09854,      0.2261054135,    0.0863280812] 
 441          ds.guess[':15@N'] = [15,   'R15N-HN',   1.34428,   0.14056,      7.83256,   0.67559,      13193.82986,   2307.09152,   28688.33492,    13480.72253,      0.110498283,     0.051923428] 
 442          ds.guess[':16@N'] = [16,   'T16N-HN',   1.71514,   0.13651,      17.44216,  0.98583,      13193.82986,   2307.09152,   57356.77617,    21892.44205,      0.220919942,     0.084322679] 
 443          ds.guess[':25@N'] = [25,   'Q25N-HN',   1.82412,   0.15809,      9.09447,   2.09215,      13193.82986,   2307.09152,   143111.13431,   49535.80302,      0.5512182797,    0.1907960569] 
 444          ds.guess[':26@N'] = [26,   'Q26N-HN',   1.45746,   0.14127,      10.22801,  0.67116,      13193.82986,   2307.09152,   28187.06876,    13359.01615,      0.1085675662,    0.051454654] 
 445          ds.guess[':28@N'] = [28,   'Q28N-HN',   1.48095,   0.14231,      10.33552,  0.691,        13193.82986,   2307.09152,   30088.0686,     13920.25654,      0.1158896091,    0.0536163723] 
 446          ds.guess[':39@N'] = [39,   'L39N-HN',   1.46094,   0.14514,      8.02194,   0.84649,      13193.82986,   2307.09152,   44130.18538,    18104.55064,      0.1699753481,    0.0697329338] 
 447          ds.guess[':40@N'] = [40,   'M40N-HN',   1.21381,   0.14035,      12.19112,  0.81418,      13193.82986,   2307.09152,   41834.90493,    17319.92156,      0.1611346625,    0.0667107938] 
 448          ds.guess[':41@N'] = [41,   'A41N-HN',   1.29296,   0.14286,      9.29941,   0.66246,      13193.82986,   2307.09152,   26694.8921,     13080.66782,      0.1028201794,    0.0503825453] 
 449          ds.guess[':43@N'] = [43,   'F43N-HN',   1.33626,   0.14352,      12.73816,  1.17386,      13193.82986,   2307.09152,   70347.63797,    26648.30524,      0.2709565833,    0.1026407417] 
 450          ds.guess[':44@N'] = [44,   'I44N-HN',   1.28487,   0.1462,       12.70158,  1.52079,      13193.82986,   2307.09152,   95616.20461,    35307.79817,      0.3682830136,    0.1359943366] 
 451          ds.guess[':45@N'] = [45,   'K45N-HN',   1.59227,   0.14591,      9.54457,   0.95596,      13193.82986,   2307.09152,   53849.7826,     21009.89973,      0.2074121253,    0.0809234085] 
 452          ds.guess[':49@N'] = [49,   'A49N-HN',   1.38521,   0.14148,      4.44842,   0.88647,      13193.82986,   2307.09152,   40686.65286,    18501.20774,      0.1567119631,    0.07126073] 
 453          ds.guess[':52@N'] = [52,   'V52N-HN',   1.57531,   0.15042,      6.51945,   1.43418,      13193.82986,   2307.09152,   93499.92172,    33233.23039,      0.3601317693,    0.1280037656] 
 454          ds.guess[':53@N'] = [53,   'A53N-HN',   1.27214,   0.13823,      4.0705,    0.85485,      13193.82986,   2307.09152,   34856.18636,    17505.02393,      0.1342548725,    0.0674237488] 
 455   
 456          # Assign guess values. 
 457          for spin, spin_id in spin_loop(return_id=True): 
 458              if spin_id in cluster_ids: 
 459                  print("spin_id %s in cluster ids"%(spin_id)) 
 460                  spin.kex = ds.guess[spin_id][6] 
 461                  spin.phi_ex = ds.guess[spin_id][10] 
 462              else: 
 463                  print("spin_id %s NOT in cluster ids"%(spin_id)) 
 464   
 465          if read_R1: 
 466              # Read the R1 data 
 467              self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
 468   
 469   
 470 -    def setup_hansen_cpmg_data(self, model=None): 
 471          """Set up the data for the test_hansen_cpmg_data_*() system tests. 
 472   
 473          @keyword model: The name of the model which will be tested. 
 474          @type model:    str 
 475          """ 
 476   
 477          # Create the data pipe and load the base data. 
 478          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
 479          self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 
 480          self.interpreter.results.read(data_path+sep+'base_pipe') 
 481          self.interpreter.deselect.spin(':4') 
 482   
 483          # Set the nuclear isotope data. 
 484          self.interpreter.spin.isotope('15N') 
 485   
 486          # Create the R2eff data pipe and load the results. 
 487          self.interpreter.pipe.create(pipe_name='R2eff - relax_disp', pipe_type='relax_disp') 
 488          self.interpreter.pipe.switch(pipe_name='R2eff - relax_disp') 
 489          self.interpreter.results.read(data_path+sep+'r2eff_pipe') 
 490          self.interpreter.deselect.spin(':4') 
 491   
 492          # The model data pipe. 
 493          pipe_name = "%s - relax_disp" % model 
 494          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 495          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 496   
 497          # Set the model. 
 498          self.interpreter.relax_disp.select_model(model=model) 
 499   
 500          # Copy the data. 
 501          self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to=pipe_name, param='r2eff') 
 502   
 503   
 504 -    def setup_kteilum_fmpoulsen_makke_cpmg_data(self, model=None, expfolder=None): 
 505          """Set up the data for the test_kteilum_fmpoulsen_makke_cpmg_data_*() system tests. 
 506   
 507          @keyword model: The name of the model which will be tested. 
 508          @type model:    str 
 509          """ 
 510   
 511          # Create the data pipe and load the base data. 
 512          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder 
 513          self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 
 514          self.interpreter.results.read(data_path+sep+'ini_setup_trunc') 
 515   
 516          # Create the R2eff data pipe and load the results. 
 517          self.interpreter.pipe.create(pipe_name='R2eff', pipe_type='relax_disp') 
 518          self.interpreter.pipe.switch(pipe_name='R2eff') 
 519          self.interpreter.results.read(data_path+sep+'r2eff_pipe_trunc') 
 520   
 521          # The model data pipe. 
 522          pipe_name = "%s - relax_disp" % model 
 523          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 524          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 525   
 526          # Set the model. 
 527          self.interpreter.relax_disp.select_model(model=model) 
 528   
 529          # Copy the data. 
 530          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
 531   
 532   
 533 -    def setup_korzhnev_2005_data(self, data_list=[]): 
 534          """Set up the data for the test_korzhnev_2005_data_*() system tests using the 'NS MMQ 2-site' model. 
 535   
 536          This loads the proton-heteronuclear SQ, ZQ, DQ, and MQ (MMQ) data from: 
 537   
 538              - Dmitry M. Korzhnev, Philipp Neudecker, Anthony Mittermaier, Vladislav Yu. Orekhov, and Lewis E. Kay (2005)  Multiple-site exchange in proteins studied with a suite of six NMR relaxation dispersion experiments: An application to the folding of a Fyn SH3 domain mutant.  127, 15602-15611 (U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}). 
 539   
 540          It consists of the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
 541   
 542   
 543          @keyword data_list: The list of data to load.  It can contain 'SQ', '1H SQ', 'ZQ', 'DQ', 'MQ', and '1H MQ'. 
 544          @type data_list:    list of str 
 545          """ 
 546   
 547          # Create the data pipe and load the base data. 
 548          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 
 549          self.interpreter.pipe.create(pipe_name='Korzhnev et al., 2005', pipe_type='relax_disp') 
 550   
 551          # Create the spin system. 
 552          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 
 553          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 
 554          self.interpreter.spin.element('H', spin_id='@H') 
 555          self.interpreter.spin.element('N', spin_id='@N') 
 556          self.interpreter.spin.isotope('1H', spin_id='@H') 
 557          self.interpreter.spin.isotope('15N', spin_id='@N') 
 558   
 559          # Define the magnetic dipole-dipole relaxation interaction. 
 560          self.interpreter.interatom.define(spin_id1=':9@N', spin_id2=':9@H', direct_bond=True) 
 561   
 562          # The spectral data - experiment ID, R2eff file name, experiment type, spin ID string, spectrometer frequency in Hertz, relaxation time. 
 563          data = [ 
 564              ['1H SQ', '1H_SQ_CPMG_500_MHz',  'hs_500.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 500e6, 0.03], 
 565              ['1H SQ', '1H_SQ_CPMG_600_MHz',  'hs_600.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 600e6, 0.03], 
 566              ['1H SQ', '1H_SQ_CPMG_800_MHz',  'hs_800.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 800e6, 0.03], 
 567              ['SQ',    '15N_SQ_CPMG_500_MHz', 'ns_500.res', EXP_TYPE_CPMG_SQ,        ':9@N', 500e6, 0.04], 
 568              ['SQ',    '15N_SQ_CPMG_600_MHz', 'ns_600.res', EXP_TYPE_CPMG_SQ,        ':9@N', 600e6, 0.04], 
 569              ['SQ',    '15N_SQ_CPMG_800_MHz', 'ns_800.res', EXP_TYPE_CPMG_SQ,        ':9@N', 800e6, 0.04], 
 570              ['DQ',    '15N_DQ_CPMG_500_MHz', 'dq_500.res', EXP_TYPE_CPMG_DQ,        ':9@N', 500e6, 0.03], 
 571              ['DQ',    '15N_DQ_CPMG_600_MHz', 'dq_600.res', EXP_TYPE_CPMG_DQ,        ':9@N', 600e6, 0.03], 
 572              ['DQ',    '15N_DQ_CPMG_800_MHz', 'dq_800.res', EXP_TYPE_CPMG_DQ,        ':9@N', 800e6, 0.03], 
 573              ['ZQ',    '15N_ZQ_CPMG_500_MHz', 'zq_500.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 500e6, 0.03], 
 574              ['ZQ',    '15N_ZQ_CPMG_600_MHz', 'zq_600.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 600e6, 0.03], 
 575              ['ZQ',    '15N_ZQ_CPMG_800_MHz', 'zq_800.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 800e6, 0.03], 
 576              ['1H MQ', '1H_MQ_CPMG_500_MHz',  'hm_500.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 500e6, 0.02], 
 577              ['1H MQ', '1H_MQ_CPMG_600_MHz',  'hm_600.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 600e6, 0.02], 
 578              ['1H MQ', '1H_MQ_CPMG_800_MHz',  'hm_800.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 800e6, 0.02], 
 579              ['MQ',    '15N_MQ_CPMG_500_MHz', 'nm_500.res', EXP_TYPE_CPMG_MQ,        ':9@N', 500e6, 0.02], 
 580              ['MQ',    '15N_MQ_CPMG_600_MHz', 'nm_600.res', EXP_TYPE_CPMG_MQ,        ':9@N', 600e6, 0.02], 
 581              ['MQ',    '15N_MQ_CPMG_800_MHz', 'nm_800.res', EXP_TYPE_CPMG_MQ,        ':9@N', 800e6, 0.02] 
 582          ] 
 583          cpmg_frqs_1h_sq = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 
 584          cpmg_frqs_sq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
 585          cpmg_frqs_dq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 
 586          cpmg_frqs_zq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 
 587          cpmg_frqs_1h_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 600.0, 700.0, 800.0, 1000.0, 1500.0, 2000.0, 2500.0] 
 588          cpmg_frqs_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
 589   
 590          # Loop over the files, reading in the data. 
 591          for data_type, id, file, exp_type, spin_id, H_frq, relax_time in data: 
 592              # Skip undesired data. 
 593              if data_type not in data_list: 
 594                  continue 
 595   
 596              # Alias the CPMG frequencies. 
 597              if data_type == 'SQ': 
 598                  cpmg_frqs = cpmg_frqs_sq 
 599              elif data_type == '1H SQ': 
 600                  cpmg_frqs = cpmg_frqs_1h_sq 
 601              elif data_type == 'DQ': 
 602                  cpmg_frqs = cpmg_frqs_dq 
 603              elif data_type == 'ZQ': 
 604                  cpmg_frqs = cpmg_frqs_zq 
 605              elif data_type == '1H MQ': 
 606                  cpmg_frqs = cpmg_frqs_1h_mq 
 607              elif data_type == 'MQ': 
 608                  cpmg_frqs = cpmg_frqs_mq 
 609   
 610              # Loop over each CPMG frequency. 
 611              for cpmg_frq in cpmg_frqs: 
 612                  # The id. 
 613                  new_id = "%s_%s" % (id, cpmg_frq) 
 614   
 615                  # Set the NMR field strength. 
 616                  self.interpreter.spectrometer.frequency(id=new_id, frq=H_frq) 
 617   
 618                  # Set the relaxation dispersion experiment type. 
 619                  self.interpreter.relax_disp.exp_type(spectrum_id=new_id, exp_type=exp_type) 
 620   
 621                  # Relaxation dispersion CPMG constant time delay T (in s). 
 622                  self.interpreter.relax_disp.relax_time(spectrum_id=new_id, time=relax_time) 
 623   
 624                  # Set the CPMG frequency. 
 625                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=new_id, cpmg_frq=cpmg_frq) 
 626   
 627              # Read the R2eff data. 
 628              self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 
 629   
 630          # Change the model. 
 631          self.interpreter.relax_disp.select_model('NS MMQ 2-site') 
 632   
 633   
 634 -    def setup_sod1wt_t25(self, pipe_name, pipe_type, pipe_name_r2eff, select_spin_index): 
 635          """Setup of data SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
 636   
 637          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
 638          'SOD1-WT' CPMG data to the CR72 dispersion model. 
 639   
 640          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
 641          Data is for experiment at 25 degree Celcius. 
 642          """ 
 643   
 644          # Create the data pipe and load the base data. 
 645          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'sod1wt_t25' 
 646   
 647          # Set experiment settings. sfrq, time_T2, ncyc 
 648          Exps = [ 
 649          ["600MHz", "Z_A", 599.8908617*1E6, 0.06, [28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 50, 18, 40, 6, 12, 0, 24], ["Z_A1", "Z_A15"] ], 
 650          ["500MHz", "Z_B", 499.862139*1E6, 0.04, [20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0], ["Z_B1", "Z_B18"] ] ] 
 651   
 652          # Create base pipe 
 653          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
 654   
 655          # Loop throug experiments 
 656          id_lists = [] 
 657          for folder, key, sfrq, time_T2, ncycs, rep_ncyss in Exps: 
 658              # Read spins 
 659              self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 
 660              self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 
 661   
 662              # Make spectrum id list 
 663              id_list = list(key+str(i) for i in range(len(ncycs))) 
 664              id_lists.append(id_list) 
 665   
 666              # Read intensities 
 667              self.interpreter.spectrum.read_intensities(file="128_FT.ser", dir=data_path+sep+folder, int_method='height', spectrum_id=id_list, int_col=list(range(len(id_list))) ) 
 668   
 669              # Loop over experiments 
 670              for i in range(len(ncycs)): 
 671                  ncyc = ncycs[i] 
 672                  vcpmg = ncyc/time_T2 
 673   
 674                  # Test if spectrum is a reference 
 675                  if float(vcpmg) == 0.0: 
 676                      vcpmg = None 
 677                  else: 
 678                      vcpmg = round(float(vcpmg), 3) 
 679   
 680                  # Set current id 
 681                  current_id = id_list[i] 
 682   
 683                  # Set the current experiment type. 
 684                  self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 
 685   
 686                  # Set the NMR field strength of the spectrum. 
 687                  self.interpreter.spectrometer.frequency(id=current_id, frq=sfrq, units='Hz') 
 688   
 689                  # Relaxation dispersion CPMG constant time delay T (in s). 
 690                  self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 
 691   
 692                  # Set the relaxation dispersion CPMG frequencies. 
 693                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 
 694   
 695          # Define replicated 
 696          self.interpreter.spectrum.replicated(spectrum_ids=Exps[0][5]) 
 697          self.interpreter.spectrum.replicated(spectrum_ids=Exps[1][5]) 
 698   
 699          # Perform error analysis 
 700          self.interpreter.spectrum.error_analysis(subset=id_lists[0]) 
 701          self.interpreter.spectrum.error_analysis(subset=id_lists[1]) 
 702   
 703          # Define isotope 
 704          self.interpreter.spin.isotope(isotope='15N') 
 705   
 706          ############# 
 707   
 708          # Define the 64 residues which was used for Global fitting 
 709          glob_assn = ["G10N-H", "D11N-H", "Q15N-H", "G16N-H", "G37N-H", "G41N-H", "L42N-H", "H43N-H", "H46N-H", "V47N-H", "E49N-H", 
 710          "E50N-H", "E51N-H", "N53N-H", "T54N-H", "G56N-H", "C57N-H", "T58N-H", "G61N-H", "H63aN-H", "F64aN-H", "N65aN-H", 
 711          "L67N-H", "S68N-H", "K70N-H", "G72N-H", "G73N-H", "K75N-H", "E78N-H", "R79N-H", "H80N-H", "V81N-H", "G82N-H", 
 712          "G85N-H", "N86N-H", "V87N-H", "S102N-H", "V103N-H", "I104N-H", "S105N-H", "A111N-H", "I112N-H", "R115N-H", 
 713          "V118N-H", "E121N-H", "A123N-H", "L126N-H", "G127N-H", "K128N-H", "G129N-H", "G130N-H", "N131N-H", "E133N-H", 
 714          "S134N-H", "T135N-H", "T137N-H", "G138N-H", "N139N-H", "A140N-H", "G141N-H", "S142N-H", "R143N-H", "C146N-H", "G147N-H"] 
 715   
 716          # Test number of global 
 717          self.assertEqual(64, len(glob_assn )) 
 718   
 719          ## Turn assignments into relax spin ids. 
 720          # Define regular expression search 
 721          r = re.compile("([a-zA-Z]+)([0-9]+)([a-zA-Z]+)") 
 722   
 723          # Create list to hold regular expression search 
 724          relax_glob_ids = [] 
 725   
 726          # Loop over assignments 
 727          for assn in glob_assn: 
 728              # Make match for the regular search 
 729              m = r.match(assn) 
 730              # Convert to relax spin string 
 731              relax_string = ":%s@%s"%(m.group(2), m.group(3)) 
 732   
 733              # Save the relax spin string and the regular search 
 734              relax_glob_ids.append([m.group(0), m.group(1), m.group(2), m.group(3), relax_string]) 
 735   
 736          ############# Deselect all spins, and select few spins 
 737   
 738          ## Deselect all spins, and select a few for analysis 
 739          self.interpreter.deselect.all() 
 740   
 741          # Select few spins 
 742          for i in select_spin_index: 
 743              self.interpreter.select.spin(spin_id=relax_glob_ids[i][4], change_all=False) 
 744   
 745          ############## 
 746   
 747          # Prepare for R2eff calculation 
 748          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
 749          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
 750   
 751          # Select model for points calculation 
 752          MODEL = "R2eff" 
 753          self.interpreter.relax_disp.select_model(model=MODEL) 
 754          # Calculate R2eff values 
 755          self.interpreter.minimise.calculate(verbosity=1) 
 756   
 757   
 758 -    def setup_missing_r1_spins(self): 
 759          """Function for setting up a few spins for the given pipe.""" 
 760   
 761          # Path to file. 
 762          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
 763   
 764          # File with spins. 
 765          file = open(data_path+sep+'R1_fitted_values.txt') 
 766          lines = file.readlines() 
 767          file.close() 
 768   
 769          for i, line in enumerate(lines): 
 770              # Make the string test 
 771              line_split = line.split() 
 772   
 773              if line_split[0] == "#": 
 774                  continue 
 775   
 776              mol_name = line_split[0] 
 777              mol_name = None 
 778              res_num = int(line_split[1]) 
 779              res_name = line_split[2] 
 780              spin_num = line_split[3] 
 781              spin_num = None 
 782              spin_name = line_split[4] 
 783   
 784              # Create the spin. 
 785              self.interpreter.spin.create(spin_name=spin_name, spin_num=spin_num, res_name=res_name, res_num=res_num, mol_name=mol_name) 
 786   
 787   
 788 -    def setup_tp02_data_to_ns_r1rho_2site(self, clustering=False): 
 789          """Setup data for the test of relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 
 790   
 791          # Reset. 
 792          self.interpreter.reset() 
 793   
 794          # Create the data pipe and load the base data. 
 795          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 
 796          self.interpreter.state.load(data_path+sep+'r2eff_values') 
 797   
 798          # The model data pipe. 
 799          model = 'NS R1rho 2-site' 
 800          pipe_name = "%s - relax_disp" % model 
 801          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 802          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 803   
 804          # Set the model. 
 805          self.interpreter.relax_disp.select_model(model=model) 
 806   
 807          # Copy the data. 
 808          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
 809   
 810          # Alias the spins. 
 811          spin1 = cdp.mol[0].res[0].spin[0] 
 812          spin2 = cdp.mol[0].res[1].spin[0] 
 813   
 814          # The R20 keys. 
 815          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
 816          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
 817   
 818          # Set the initial parameter values. 
 819          spin1.r2 = {r20_key1: 9.9963793866185, r20_key2: 15.0056724422684} 
 820          spin1.pA = 0.779782428085762 
 821          spin1.dw = 7.57855284496424 
 822          spin1.kex = 1116.7911285203 
 823          spin2.r2 = {r20_key1: 11.9983346935434, r20_key2: 18.0076097513337} 
 824          spin2.pA = 0.826666229688602 
 825          spin2.dw = 9.5732624231366 
 826          spin2.kex = 1380.46162655657 
 827   
 828          # Test the values when clustering. 
 829          if clustering: 
 830              self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-100") 
 831   
 832          # Low precision optimisation. 
 833          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
 834   
 835          # Printout. 
 836          print("\n\nOptimised parameters:\n") 
 837          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
 838          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
 839          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
 840          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
 841          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
 842          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
 843          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
 844   
 845   
 846 -    def test_baldwin_synthetic(self): 
 847          """Test synthetic data of Andrew J. Baldwin B14 model  whereby the simplification R20A = R20B is assumed. 
 848   
 849          Support requst sr #3154 U{https://gna.org/support/index.php?3154}. 
 850   
 851          This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>} with R20A, R20B = 2. rad/s. 
 852          """ 
 853   
 854          # The path to the data files. 
 855          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 
 856   
 857          # Create pipe 
 858          pipe_name = 'base pipe' 
 859          pipe_type = 'relax_disp' 
 860          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
 861   
 862          # Create base pipe 
 863          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
 864   
 865          # Generate the sequence. 
 866          self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 
 867   
 868          # Define the isotope. 
 869          self.interpreter.spin.isotope('1H', spin_id='@H') 
 870   
 871          # Build the experiment IDs. 
 872          # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 
 873          ncycs = [2, 4, 8, 10, 20, 40, 500] 
 874          ids = [] 
 875          for ncyc in ncycs: 
 876              ids.append('CPMG_%s' % ncyc) 
 877   
 878          print("\n\nThe experiment IDs are %s." % ids) 
 879   
 880          # Set up the metadata for the experiments. 
 881          # This value is used in Baldwin.py. It is the 1H Larmor frequency. 
 882          sfrq = 200. * 1E6 
 883   
 884          # Total time of CPMG block. 
 885          Trelax = 0.04 
 886   
 887          # First set the 
 888          for i in range(len(ids)): 
 889              id = ids[i] 
 890              # Set the spectrometer frequency. 
 891              self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 
 892   
 893              # Set the experiment type. 
 894              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
 895   
 896              # Set the relaxation dispersion CPMG constant time delay T (in s). 
 897              self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 
 898   
 899              # Set the relaxation dispersion CPMG frequencies. 
 900              ncyc = ncycs[i] 
 901              nu_cpmg = ncyc / Trelax 
 902              self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 
 903   
 904          # Prepare for R2eff reading. 
 905          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
 906          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
 907   
 908          # Try reading the R2eff file. 
 909          self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_r2a_eq_r2b_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 
 910   
 911          # Check the global data. 
 912          data = [ 
 913              ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 
 914              ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 
 915              ['dispersion_points', len(ncycs)], 
 916              ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 
 917              ['exp_type_list', ['SQ CPMG']], 
 918              ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 
 919              ['spectrometer_frq_count', 1], 
 920              ['spectrometer_frq_list', [sfrq]], 
 921              ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 
 922          ] 
 923          for name, value in data: 
 924              # Does it exist? 
 925              self.assert_(hasattr(cdp, name)) 
 926   
 927              # Check the object. 
 928              obj = getattr(cdp, name) 
 929              if not isinstance(data, dict): 
 930                  self.assertEqual(obj, value) 
 931   
 932              # Check the global dictionary data. 
 933              else: 
 934                  for id in ids: 
 935                      self.assertEqual(obj[id], value[id]) 
 936   
 937          # Check the spin data. 
 938          n_data = [ 
 939              [ 50.000000, 10.367900, 0.1], 
 940              [ 100.000000, 10.146849, 0.1], 
 941              [ 200.000000, 9.765987, 0.1], 
 942              [ 250.000000, 9.409789, 0.1], 
 943              [ 500.000000, 5.829819, 0.1], 
 944              [ 1000.000000, 3.191928, 0.1], 
 945              [ 12500.000000, 2.008231, 0.1] 
 946          ] 
 947          for disp_point, value, error in n_data: 
 948              id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 
 949              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
 950              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
 951   
 952          # Generate r20 key. 
 953          r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 
 954   
 955          ## Now prepare for MODEL calculation. 
 956          MODEL = "B14" 
 957   
 958          # Change pipe. 
 959          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
 960          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
 961          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
 962   
 963          # Then select model. 
 964          self.interpreter.relax_disp.select_model(model=MODEL) 
 965   
 966          # Store grid and minimisations results. 
 967          grid_results = [] 
 968          mini_results = [] 
 969   
 970          # The grid search size (the number of increments per dimension). 
 971          # If None, use the default values. 
 972          #GRID = None 
 973          GRID = 13 
 974          # Perform Grid Search. 
 975          if GRID: 
 976              # Set the R20 parameters in the default grid search using the minimum R2eff value. 
 977              # This speeds it up considerably. 
 978              self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
 979   
 980              # Then do grid search. 
 981              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 
 982   
 983              # If no Grid search, set the default values. 
 984          else: 
 985              for param in MODEL_PARAMS[MODEL]: 
 986                  self.interpreter.value.set(param=param, index=None) 
 987                  # Do a grid search, which will store the chi2 value. 
 988              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 
 989   
 990          # Store result. 
 991          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
 992              grid_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
 993   
 994          ## Now do minimisation. 
 995          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
 996          set_func_tol = 1e-10 
 997          set_max_iter = 1000 
 998          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
 999   
1000          # Store result. 
1001          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1002              mini_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1003   
1004          # Print results. 
1005          for i in range(len(grid_results)): 
1006              g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
1007              m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
1008              print("GRID %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
1009              print("MIN  %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
1010   
1011          # Reference values from Baldwin.py. 
1012          # Exchange rate = k+ + k- (s-1) 
1013          kex = 1000. 
1014          # Fractional population of excited state k+/kex 
1015          pb = 0.01 
1016          # deltaOmega in ppm 
1017          dw_ppm = 2. 
1018          #relaxation rate of ground (s-1) 
1019          R2g = 2. 
1020          #relaxation rate of excited (s-1) 
1021          R2e = 2. 
1022   
1023          # Test the parameters which created the data. 
1024          # This is for the 1H spin. 
1025          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2[r20_key], R2g, 6) 
1026   
1027          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 
1028          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 8) 
1029          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex, kex, 3) 
1030   
1031   
1032 -    def test_baldwin_synthetic_full(self): 
1033          """Test synthetic data of Andrew J. Baldwin B14 model. Support requst sr #3154 U{https://gna.org/support/index.php?3154}. 
1034   
1035          This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>}. 
1036          """ 
1037   
1038          # The path to the data files. 
1039          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 
1040   
1041          # Create pipe 
1042          pipe_name = 'base pipe' 
1043          pipe_type = 'relax_disp' 
1044          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
1045   
1046          # Create base pipe 
1047          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
1048   
1049          # Generate the sequence. 
1050          # Generate both a 1H spin, and 15N spin. 
1051          self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 
1052   
1053          # Define the isotope. 
1054          self.interpreter.spin.isotope('1H', spin_id='@H') 
1055   
1056          # Build the experiment IDs. 
1057          # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 
1058          ncycs = [2, 4, 8, 10, 20, 40, 500] 
1059          ids = [] 
1060          for ncyc in ncycs: 
1061              ids.append('CPMG_%s' % ncyc) 
1062   
1063          print("\n\nThe experiment IDs are %s." % ids) 
1064   
1065          # Set up the metadata for the experiments. 
1066          # This value is used in Baldwin.py. It is the 1H Larmor frequency. 
1067          sfrq = 200. * 1E6 
1068   
1069          # Total time of CPMG block. 
1070          Trelax = 0.04 
1071   
1072          # First set the 
1073          for i in range(len(ids)): 
1074              id = ids[i] 
1075              # Set the spectrometer frequency. 
1076              self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 
1077   
1078              # Set the experiment type. 
1079              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
1080   
1081              # Set the relaxation dispersion CPMG constant time delay T (in s). 
1082              self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 
1083   
1084              # Set the relaxation dispersion CPMG frequencies. 
1085              ncyc = ncycs[i] 
1086              nu_cpmg = ncyc / Trelax 
1087              self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 
1088   
1089          # Prepare for R2eff reading. 
1090          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
1091          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
1092   
1093          # Try reading the R2eff file. 
1094          self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 
1095   
1096          # Check the global data. 
1097          data = [ 
1098              ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 
1099              ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 
1100              ['dispersion_points', len(ncycs)], 
1101              ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 
1102              ['exp_type_list', ['SQ CPMG']], 
1103              ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 
1104              ['spectrometer_frq_count', 1], 
1105              ['spectrometer_frq_list', [sfrq]], 
1106              ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 
1107          ] 
1108          for name, value in data: 
1109              # Does it exist? 
1110              self.assert_(hasattr(cdp, name)) 
1111   
1112              # Check the object. 
1113              obj = getattr(cdp, name) 
1114              if not isinstance(data, dict): 
1115                  self.assertEqual(obj, value) 
1116   
1117              # Check the global dictionary data. 
1118              else: 
1119                  for id in ids: 
1120                      self.assertEqual(obj[id], value[id]) 
1121   
1122          # Check the spin data. 
1123          n_data = [ 
1124              [ 50.000000, 10.286255, 0.1], 
1125              [ 100.000000, 10.073083, 0.1], 
1126              [ 200.000000, 9.692746, 0.1], 
1127              [ 250.000000, 9.382441, 0.1], 
1128              [ 500.000000, 6.312396, 0.1], 
1129              [ 1000.000000, 3.957029, 0.1], 
1130              [ 12500.000000, 2.880420, 0.1] 
1131          ] 
1132          for disp_point, value, error in n_data: 
1133              id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 
1134              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
1135              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
1136   
1137          # Generate r20 key. 
1138          r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 
1139   
1140          ## Now prepare for MODEL calculation. 
1141          MODEL = "B14 full" 
1142   
1143          # Change pipe. 
1144          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
1145          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
1146          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
1147   
1148          # Then select model. 
1149          self.interpreter.relax_disp.select_model(model=MODEL) 
1150   
1151          # Store grid and minimisations results. 
1152          grid_results = [] 
1153          mini_results = [] 
1154          clust_results = [] 
1155   
1156          # The grid search size (the number of increments per dimension). 
1157          # If None, use the default values. 
1158          #GRID = None 
1159          GRID = 13 
1160          # Perform Grid Search. 
1161          if GRID: 
1162              # Set the R20 parameters in the default grid search using the minimum R2eff value. 
1163              # This speeds it up considerably. 
1164              self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
1165   
1166              # Then do grid search. 
1167              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 
1168   
1169              # If no Grid search, set the default values. 
1170          else: 
1171              for param in MODEL_PARAMS[MODEL]: 
1172                  self.interpreter.value.set(param=param, index=None) 
1173                  # Do a grid search, which will store the chi2 value. 
1174              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 
1175   
1176          # Store result. 
1177          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1178              grid_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1179   
1180          ## Now do minimisation. 
1181          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
1182          set_func_tol = 1e-11 
1183          set_max_iter = 10000 
1184          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1185   
1186          # Store result. 
1187          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1188              mini_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1189   
1190          print("\n# Now print before and after minimisation-\n") 
1191   
1192          # Print results. 
1193          for i in range(len(grid_results)): 
1194              g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
1195              m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
1196              print("GRID %s r2a=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
1197              print("MIN  %s r2b=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
1198   
1199          # Reference values from Baldwin.py. 
1200          # Exchange rate = k+ + k- (s-1) 
1201          kex = 1000. 
1202          # Fractional population of excited state k+/kex 
1203          pb = 0.01 
1204          # deltaOmega in ppm 
1205          dw_ppm = 2. 
1206          #relaxation rate of ground (s-1) 
1207          R2g = 2. 
1208          #relaxation rate of excited (s-1) 
1209          R2e = 100. 
1210   
1211          # Test the parameters which created the data. 
1212          # This is for the 1H spin. 
1213          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2a[r20_key], R2g, 3) 
1214          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2b[r20_key]/100, R2e/100, 3) 
1215   
1216          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 
1217          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 6) 
1218          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex/1000, kex/1000, 2) 
1219   
1220   
1221 -    def x_test_bmrb_sub_cpmg(self): 
1222          """U{Task #7858: <https://gna.org/task/?7858>} Make it possible to submit CPMG experiments for BMRB. 
1223          This uses CPMG data from: 
1224              - Webb H, Tynan-Connolly BM, Lee GM, Farrell D, O'Meara F, Soendergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE. 
1225                Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. 
1226                (2011), Proteins: Struct, Funct, Bioinf 79(3):685-702, DOI 10.1002/prot.22886 
1227          """ 
1228   
1229          # Define path to data  
1230          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'HWebb_KTeilum_Proteins_Struct_Funct_Bioinf_2011' 
1231   
1232          # Read data. 
1233          self.interpreter.results.read(prev_data_path + sep + 'FT_-_CR72_-_min_-_128_-_free_spins') 
1234   
1235          # Set element 
1236          self.interpreter.spin.element(element='N', spin_id=':*@N', force=False) 
1237          #self.interpreter.spin.isotope(isotope='15N', spin_id=':*@N', force=False) 
1238          # Rename molecule from None to 'HEWL' 
1239          self.interpreter.molecule.name(mol_id=None, name='HEWL', force=True) 
1240          self.interpreter.molecule.type(mol_id='#HEWL', type='protein', force=False) 
1241   
1242          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1243              print(spin_id) 
1244              if resn == 'C': 
1245                  print(resi, resn) 
1246   
1247          # Select the thiol state of the system. 
1248          # 'all disulfide bound', 'all free', 'all other bound', 'disulfide and other bound', 'free and disulfide bound', 'free and other bound', 'free disulfide and other bound', 'not available', 'not present', 'not reported', 'unknown' 
1249          self.interpreter.bmrb.thiol_state(state='not reported') 
1250   
1251          # relax_data.temp_calibration(ri_id=None, method=None) 
1252   
1253          # Call display of bmrb. 
1254          self.interpreter.bmrb.display() 
1255   
1256   
1257 -    def test_bug_21081_disp_cluster_fail(self): 
1258          """U{Bug #21081<https://gna.org/bugs/?21081>} catch, the failure of a cluster analysis when spins are deselected.""" 
1259   
1260          # Clear the data store. 
1261          self.interpreter.reset() 
1262   
1263          # Load the state. 
1264          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21081_disp_cluster_fail.bz2' 
1265          self.interpreter.state.load(state, force=True) 
1266   
1267          # Model selection - to catch the failure. 
1268          self.interpreter.model_selection(method='AIC', modsel_pipe='final', bundle='relax_disp', pipes=['No Rex', 'CR72']) 
1269   
1270   
1271 -    def test_bug_21460_disp_cluster_fail(self): 
1272          """U{Bug #21460<https://gna.org/bugs/?21460>} catch, the failure due to a spectrometer frequency having no relaxation data.""" 
1273   
1274          # Clear the data store. 
1275          self.interpreter.reset() 
1276   
1277          # Load the state. 
1278          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21460_bad_fields.bz2' 
1279          self.interpreter.state.load(state, force=True) 
1280   
1281          # Execute the auto-analysis (fast). 
1282          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1283          relax_disp.Relax_disp.opt_max_iterations = 1000 
1284          relax_disp.Relax_disp(pipe_name="origin - relax_disp (Thu Jan  2 13:46:44 2014)", pipe_bundle="relax_disp (Thu Jan  2 13:46:44 2014)", results_dir=self.tmpdir, models=['R2eff', 'No Rex', 'CR72', 'NS CPMG 2-site expanded'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1285   
1286   
1287 -    def test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp(self): 
1288          """U{Bug #21665<https://gna.org/bugs/?21344>} catch, the failure of an analysis of a sparse acquired R1rho dataset with missing combinations of time and spin-lock field strengths using auto_analysis.""" 
1289   
1290          # Clear the data store. 
1291          self.interpreter.reset() 
1292   
1293          # Load the state. 
1294          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
1295          self.interpreter.state.load(state, force=True) 
1296   
1297          # Execute the auto-analysis (fast). 
1298          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1299          relax_disp.Relax_disp.opt_max_iterations = 1000 
1300          relax_disp.Relax_disp(pipe_name='base pipe', pipe_bundle='relax_disp', results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1301   
1302   
1303 -    def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_calc(self): 
1304          """U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times, using minimise.calculate().""" 
1305   
1306          # Clear the data store. 
1307          self.interpreter.reset() 
1308   
1309          # Load the state. 
1310          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 
1311          self.interpreter.state.load(state, force=True) 
1312   
1313          # Run the calculation. 
1314          self.interpreter.minimise.calculate(verbosity=1) 
1315   
1316   
1317 -    def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_relax_disp(self): 
1318          """U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times using auto_analysis.""" 
1319   
1320          # Clear the data store. 
1321          self.interpreter.reset() 
1322   
1323          # Load the state. 
1324          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 
1325          self.interpreter.state.load(state, force=True) 
1326   
1327          # Execute the auto-analysis (fast). 
1328          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1329          relax_disp.Relax_disp.opt_max_iterations = 1000 
1330          relax_disp.Relax_disp(pipe_name="compare_128_FT_R2eff", pipe_bundle="cpmg_disp_sod1d90a", results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1331   
1332   
1333 -    def test_bug_21715_clustered_indexerror(self): 
1334          """Catch U{bug #21715<https://gna.org/bugs/?21715>}, the failure of a clustered auto-analysis due to an IndexError.""" 
1335   
1336          # Clear the data store. 
1337          self.interpreter.reset() 
1338   
1339          # Load the state. 
1340          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'state.bz2' 
1341          self.interpreter.state.load(state, force=True) 
1342   
1343          # Execute the auto-analysis (fast). 
1344          pre_run_dir = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'non_clustered' 
1345          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1346          relax_disp.Relax_disp.opt_max_iterations = 1000 
1347          relax_disp.Relax_disp(pipe_name='origin - relax_disp (Sun Feb 23 19:36:51 2014)', pipe_bundle='relax_disp (Sun Feb 23 19:36:51 2014)', results_dir=self.tmpdir, models=['R2eff', 'No Rex'], grid_inc=11, mc_sim_num=3, modsel='AIC', pre_run_dir=pre_run_dir, insignificance=1.0, numeric_only=True, mc_sim_all_models=False, eliminate=True) 
1348   
1349   
1350 -    def test_bug_22146_unpacking_r2a_r2b_cluster_B14(self): 
1351          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered B14 full analysis.""" 
1352   
1353          # Base data setup. 
1354          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='B14_full', model_analyse = MODEL_B14_FULL) 
1355   
1356   
1357 -    def test_bug_22146_unpacking_r2a_r2b_cluster_CR72(self): 
1358          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered CR72 full analysis.""" 
1359   
1360          # Base data setup. 
1361          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='CR72_full', model_analyse = MODEL_CR72_FULL) 
1362   
1363   
1364 -    def test_bug_22146_unpacking_r2a_r2b_cluster_NS_3D(self): 
1365          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE 3D full analysis.""" 
1366   
1367          # Base data setup. 
1368          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_3d_full', model_analyse = MODEL_NS_CPMG_2SITE_3D_FULL) 
1369   
1370   
1371 -    def test_bug_22146_unpacking_r2a_r2b_cluster_NS_STAR(self): 
1372          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE STAR full analysis.""" 
1373   
1374          # Base data setup. 
1375          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_star_full', model_analyse = MODEL_NS_CPMG_2SITE_STAR_FULL, places = 4) 
1376   
1377   
1378 -    def test_bug_22477_grace_write_k_AB_mixed_analysis(self): 
1379          """Catch U{bug #22146<https://gna.org/bugs/?22477>}, the failure of issuing: grace.write(x_data_type='res_num', y_data_type=param) for a mixed CPMG analysis.""" 
1380   
1381          # Clear the data store. 
1382          self.interpreter.reset() 
1383   
1384          # Load the state. 
1385          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22477_grace_write_k_AB_mixed_analysis'+sep+'bug_22477_results.bz2' 
1386          self.interpreter.state.load(state, force=True) 
1387   
1388          param = 'k_AB' 
1389   
1390          for spin, spin_id in spin_loop(return_id=True, skip_desel=True): 
1391              print(spin_id, spin.params) 
1392              if param in spin.params: 
1393                  print(spin_id, spin.k_AB, spin.k_AB_err) 
1394   
1395          # Perform write. 
1396          self.interpreter.grace.write(x_data_type='res_num', y_data_type=param, file='%s.agr'%param, dir=self.tmpdir, force=True) 
1397   
1398   
1399          # Test the header of the value.write  parameter r2. 
1400          param = 'r2' 
1401          self.interpreter.value.write(param=param, file='%s.out'%param, dir=self.tmpdir, force=True) 
1402   
1403          file = open(self.tmpdir+sep+'%s.out'%param) 
1404          lines = file.readlines() 
1405          file.close() 
1406   
1407          for i, line in enumerate(lines): 
1408              # Make the string test 
1409              line_split = line.split() 
1410              print(line_split) 
1411   
1412              if len(line_split) > 1: 
1413                  # Break at parameter header. 
1414                  if line_split[0] == "#" and line_split[1] == 'mol_name': 
1415                      nr_split_header = len(line_split) 
1416                      nr_split_header_i = i 
1417                      break 
1418   
1419          # Call the line after. 
1420          line_split_val = lines[nr_split_header_i + 1].split() 
1421          print(line_split_val) 
1422   
1423          # Assert that the number of columns is equal, plus 1 for "#". 
1424          self.assertEqual(nr_split_header, len(line_split_val) + 1) 
1425   
1426          # Test the header of the value.write for parameter r2eff. 
1427          param = 'r2eff' 
1428          self.interpreter.value.write(param=param, file='%s.out'%param, dir=self.tmpdir, force=True) 
1429   
1430          file = open(self.tmpdir+sep+'%s.out'%param) 
1431          lines = file.readlines() 
1432          file.close() 
1433   
1434          for i, line in enumerate(lines): 
1435              # Make the string test 
1436              line_split = line.split() 
1437              print(line_split) 
1438   
1439              if len(line_split) > 1: 
1440                  # Break at parameter header. 
1441                  if line_split[0] == "#" and line_split[1] == 'mol_name': 
1442                      nr_split_header = len(line_split) 
1443                      nr_split_header_i = i 
1444                      break 
1445   
1446          # Call the line after. 
1447          line_split_val = lines[nr_split_header_i + 1].split() 
1448          print(line_split_val) 
1449   
1450          # Assert that the number of columns is equal, plus 1 for "#". 
1451          self.assertEqual(nr_split_header, len(line_split_val) + 1) 
1452   
1453   
1454 -    def test_bug_23186_cluster_error_calc_dw(self): 
1455          """Catch U{bug #23186<https://gna.org/bugs/?23186>}: Error calculation of individual parameter "dw" from Monte-Carlo, is based on first spin.""" 
1456   
1457          # Clear the data store. 
1458          self.interpreter.reset() 
1459   
1460          # Load the state. 
1461          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_23186.bz2' 
1462          self.interpreter.state.load(state, force=True) 
1463   
1464          # Dic key to spectrometer frq. 
1465          dickey = 'SQ CPMG - 599.89086220 MHz' 
1466   
1467          # First get the resi 0 array of sim r2a. 
1468          resi_0_r2a = [] 
1469   
1470          # Loop over the dics in spin. 
1471          for cdic in cdp.mol[0].res[0].spin[0].r2a_sim: 
1472              resi_0_r2a.append(cdic[dickey]) 
1473   
1474          # Get stats with numpy 
1475          resi_0_r2a_std = std(asarray(resi_0_r2a), ddof=1) 
1476   
1477          # First get the resi 86 array of sim r2a. 
1478          resi_86_r2a = [] 
1479   
1480          # Loop over the dics in spin. 
1481          for cdic in cdp.mol[0].res[1].spin[0].r2a_sim: 
1482              resi_86_r2a.append(cdic[dickey]) 
1483   
1484          # Get stats with numpy 
1485          resi_86_r2a_std = std(asarray(resi_86_r2a), ddof=1) 
1486   
1487          # Then get for dw. 
1488   
1489          # First get the array of sim dw. 
1490          resi_0_dw = cdp.mol[0].res[0].spin[0].dw_sim 
1491          resi_86_dw = cdp.mol[0].res[1].spin[0].dw_sim 
1492   
1493          # Get stats with numpy 
1494          resi_0_dw_std = std(asarray(resi_0_dw), ddof=1) 
1495          resi_86_dw_std = std(asarray(resi_86_dw), ddof=1) 
1496   
1497          # Then get for spin independent parameter. 
1498   
1499          # First get the array of sim dw. 
1500          resi_0_kAB = cdp.mol[0].res[0].spin[0].k_AB_sim 
1501          resi_86_kAB = cdp.mol[0].res[1].spin[0].k_AB_sim 
1502   
1503          # Get stats with numpy 
1504          resi_0_kAB_std = std(asarray(resi_0_kAB), ddof=1) 
1505          resi_86_kAB_std = std(asarray(resi_0_kAB), ddof=1) 
1506   
1507          # Assume they both std of k_AB values are equal 
1508          self.assertEqual(resi_0_kAB_std, resi_86_kAB_std) 
1509   
1510          # Perform error analysis. 
1511          self.interpreter.monte_carlo.error_analysis() 
1512   
1513          # Check values for k_AB. 
1514          self.assertAlmostEqual(resi_0_kAB_std, cdp.mol[0].res[0].spin[0].k_AB_err) 
1515          self.assertAlmostEqual(resi_86_kAB_std, cdp.mol[0].res[1].spin[0].k_AB_err) 
1516   
1517          # Check values for r2a. 
1518          self.assertAlmostEqual(resi_0_r2a_std, cdp.mol[0].res[0].spin[0].r2a_err[dickey]) 
1519          self.assertAlmostEqual(resi_86_r2a_std, cdp.mol[0].res[1].spin[0].r2a_err[dickey]) 
1520   
1521          # Check values for dw. 
1522          self.assertAlmostEqual(resi_0_dw_std, cdp.mol[0].res[0].spin[0].dw_err) 
1523          self.assertAlmostEqual(resi_86_dw_std, cdp.mol[0].res[1].spin[0].dw_err) 
1524   
1525   
1526 -    def test_bug_9999_slow_r1rho_r2eff_error_with_mc(self): 
1527          """Catch U{bug #9999<https://gna.org/bugs/?9999>}, The slow optimisation of R1rho R2eff error estimation with Monte Carlo simulations.""" 
1528   
1529          # Define path to data  
1530          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff" 
1531   
1532          # Read data. 
1533          self.interpreter.results.read(prev_data_path + sep + 'results')         
1534   
1535          # Now count number 
1536          graph_nr = 1 
1537          for exp_type, frq, offset, point in loop_exp_frq_offset_point(return_indices=False): 
1538              print("\nGraph nr %i" % graph_nr) 
1539              for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
1540                  print(exp_type, frq, offset, point, time) 
1541              graph_nr += 1 
1542   
1543          ## Possibly do an error analysis. 
1544   
1545          # Check if intensity errors have already been calculated by the user. 
1546          precalc = True 
1547          for spin in spin_loop(skip_desel=True): 
1548              # No structure. 
1549              if not hasattr(spin, 'peak_intensity_err'): 
1550                  precalc = False 
1551                  break 
1552   
1553              # Determine if a spectrum ID is missing from the list. 
1554              for id in cdp.spectrum_ids: 
1555                  if id not in spin.peak_intensity_err: 
1556                      precalc = False 
1557                      break 
1558   
1559          # Skip. 
1560          if precalc: 
1561              print("Skipping the error analysis as it has already been performed.") 
1562   
1563          else: 
1564              # Loop over the spectrometer frequencies. 
1565              for frq in loop_frq(): 
1566                  # Generate a list of spectrum IDs matching the frequency. 
1567                  ids = [] 
1568                  for id in cdp.spectrum_ids: 
1569                      # Check that the spectrometer frequency matches. 
1570                      match_frq = True 
1571                      if frq != None and cdp.spectrometer_frq[id] != frq: 
1572                          match_frq = False 
1573   
1574                      # Add the ID. 
1575                      if match_frq: 
1576                          ids.append(id) 
1577   
1578                  # Run the error analysis on the subset. 
1579                  self.interpreter.spectrum.error_analysis(subset=ids) 
1580   
1581          print("has_exponential_exp_type:", has_exponential_exp_type()) 
1582   
1583          model = 'R2eff' 
1584          self.interpreter.relax_disp.select_model(model) 
1585   
1586          for spin, spin_id in spin_loop(return_id=True, skip_desel=True): 
1587              #delattr(spin, 'r2eff') 
1588              #delattr(spin, 'r2eff_err') 
1589              #delattr(spin, 'i0') 
1590              #delattr(spin, 'i0_err') 
1591              setattr(spin, 'r2eff', {}) 
1592              setattr(spin, 'r2eff_err', {}) 
1593              setattr(spin, 'i0', {}) 
1594              setattr(spin, 'i0_err', {}) 
1595   
1596          # Do Grid Search 
1597          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=21, constraints=True, verbosity=1) 
1598   
1599          # Start dic. 
1600          my_dic = {} 
1601   
1602          # Define counter for maximum elements in the numpy array list 
1603          NE = 0 
1604          NS = 1 
1605          NM = 0 
1606          NO = 0 
1607          ND = 0 
1608          NT = 0 
1609   
1610          for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1611              # Save to counter. 
1612              if ei > NE: 
1613                  NE = ei 
1614              if mi > NM: 
1615                  NM = mi 
1616              if oi > NO: 
1617                  NO = oi 
1618              if di > ND: 
1619                 ND = di 
1620   
1621              for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1622                  # Save to counter. 
1623                  if ti > NT: 
1624                      NT = ti 
1625   
1626          # Add 1 to counter, since index start from 0. 
1627          NE = NE + 1 
1628          NM = NM + 1  
1629          NO = NO + 1 
1630          ND = ND + 1 
1631          NT = NT + 1 
1632   
1633          # Make data array. 
1634          values_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1635          errors_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1636          times_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1637          struct_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1638          param_key_list = [] 
1639   
1640   
1641          # Loop over each spectrometer frequency and dispersion point. 
1642          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1643              # Add key to dic. 
1644              my_dic[spin_id] = {} 
1645   
1646              # Generate spin string. 
1647              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1648   
1649              # Loop over the parameters. 
1650              #print("Grid optimised parameters for spin: %s" % (spin_string)) 
1651   
1652              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1653                  # Generate the param_key. 
1654                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1655   
1656                  # Append key. 
1657                  param_key_list.append(param_key) 
1658   
1659                  # Add key to dic. 
1660                  my_dic[spin_id][param_key] = {} 
1661   
1662                  # Get the value. 
1663                  R2eff_value = getattr(cur_spin, 'r2eff')[param_key] 
1664                  i0_value = getattr(cur_spin, 'i0')[param_key] 
1665   
1666                  # Save to dic. 
1667                  my_dic[spin_id][param_key]['R2eff_value_grid'] = R2eff_value 
1668                  my_dic[spin_id][param_key]['i0_value_grid'] = i0_value 
1669   
1670                  ## Now try do a line of best fit by least squares. 
1671                  # The peak intensities, errors and times. 
1672                  values = [] 
1673                  errors = [] 
1674                  times = [] 
1675                  for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1676                      value = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, sim_index=None) 
1677                      values.append(value) 
1678   
1679                      error = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True) 
1680                      errors.append(error) 
1681                      times.append(time) 
1682   
1683                      # Save to numpy arrays. 
1684                      values_arr[ei, 0, mi, oi, di, ti] = value 
1685                      errors_arr[ei, 0, mi, oi, di, ti] = error 
1686                      times_arr[ei, 0, mi, oi, di, ti] = time 
1687                      struct_arr[ei, 0, mi, oi, di, ti] = 1.0 
1688   
1689                  # y= A exp(x * k) 
1690                  # w[i] = ln(y[i]) 
1691                  # int[i] = i0 * exp( - times[i] * r2eff); 
1692                  w = log(array(values)) 
1693                  x = - array(times) 
1694                  n = len(times) 
1695   
1696                  b = (sum(x*w) - 1./n * sum(x) * sum(w) ) / ( sum(x**2) - 1./n * (sum(x))**2 ) 
1697                  a = 1./n * sum(w) - b * 1./n * sum(x) 
1698                  R2eff_est = b 
1699                  i0_est = exp(a) 
1700   
1701                  my_dic[spin_id][param_key]['R2eff_est'] = R2eff_est 
1702                  my_dic[spin_id][param_key]['i0_est'] = i0_est 
1703   
1704                  # Print value. 
1705                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'R2eff', "Value : Estimated:", R2eff_value, R2eff_est)) 
1706                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0', "Value: Estimated:", i0_value, i0_est)) 
1707   
1708   
1709          # Do minimisation. 
1710          set_func_tol = 1e-25 
1711          set_max_iter = int(1e7) 
1712          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1713   
1714          # Loop over each spectrometer frequency and dispersion point. 
1715          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1716              # Generate spin string. 
1717              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1718   
1719              # Loop over the parameters. 
1720              print("Optimised parameters for spin: %s" % (spin_string)) 
1721   
1722              for exp_type, frq, offset, point in loop_exp_frq_offset_point(): 
1723                  # Generate the param_key. 
1724                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1725   
1726                  # Get the value. 
1727                  R2eff_value = getattr(cur_spin, 'r2eff')[param_key] 
1728                  i0_value = getattr(cur_spin, 'i0')[param_key] 
1729   
1730                  # Extract from dic. 
1731                  R2eff_value_grid = my_dic[spin_id][param_key]['R2eff_value_grid'] 
1732                  i0_value_grid = my_dic[spin_id][param_key]['i0_value_grid'] 
1733                  R2eff_est = my_dic[spin_id][param_key]['R2eff_est'] 
1734                  i0_est = my_dic[spin_id][param_key]['i0_est'] 
1735   
1736                  # Print value. 
1737                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'R2eff', "Value : Estimated:", R2eff_value, R2eff_est)) 
1738                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0', "Value: Estimated:", i0_value, i0_est)) 
1739   
1740                  print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:", 'R2eff', "Grid : Min : Estimated:", R2eff_value_grid, R2eff_value, R2eff_est)) 
1741                  print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:", 'i0', "Grid : Min : Estimated:", i0_value_grid, i0_value, i0_est)) 
1742   
1743          print(NE, NS, NM, NO, ND, NT) 
1744          for param_key in param_key_list: 
1745              print("        '%s'," % param_key) 
1746          print(values_arr.shape) 
1747   
1748          # Save arrays to profiling. 
1749          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'curve_fitting'+sep+'profiling'+sep 
1750          #save(data_path + "values_arr", values_arr) 
1751          #save(data_path + "errors_arr", errors_arr) 
1752          #save(data_path + "times_arr", times_arr) 
1753          #save(data_path + "struct_arr", struct_arr) 
1754   
1755   
1756 -    def test_bug_atul_srivastava(self): 
1757          """Test data from Atul Srivastava.  This is a bug missing raising a Relax Error, since the setup points to a situation where the data 
1758          shows it is exponential fitting, but only one time point is added per file. 
1759   
1760          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1718>}: 
1761          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1735>}: 
1762          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1735/focus=1736>}: 
1763   
1764          """ 
1765   
1766          # Data path. 
1767          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_Atul_Srivastava' 
1768          file = data_path + sep + 'bug_script.py' 
1769   
1770          # Run script. 
1771          self.interpreter.script(file=file, dir=None) 
1772   
1773          # The grid search size (the number of increments per dimension). 
1774          GRID_INC = 11 
1775   
1776          # Check-data. 
1777          ################# 
1778   
1779          # Loop over spins, to see current setup. 
1780          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1781              print(mol_name, resi, resn, spin_id) 
1782   
1783          # Loop over setup. 
1784          for id in cdp.exp_type: 
1785              print(id, cdp.exp_type[id], cdp.spectrometer_frq[id], cdp.spin_lock_offset[id], cdp.spin_lock_nu1[id]) 
1786   
1787   
1788          # Manual minimisation. 
1789          ################# 
1790          if True: 
1791              # Set the model. 
1792              self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
1793   
1794              # Check if intensity errors have already been calculated. 
1795              check_intensity_errors() 
1796   
1797              # Calculate the R2eff values for the fixed relaxation time period data types. 
1798              if cdp.model_type == MODEL_R2EFF and not has_exponential_exp_type(): 
1799                  self.interpreter.minimise.calculate() 
1800   
1801              # Optimise the model. 
1802              else: 
1803                  constraints = False 
1804                  min_algor = 'Newton' 
1805                  self.assertRaises(RelaxError, self.interpreter.minimise.grid_search, inc=GRID_INC) 
1806                  self.assertRaises(RelaxError, self.interpreter.minimise.execute, min_algor=min_algor, constraints=constraints) 
1807   
1808          # Inspect. 
1809          if False: 
1810              # Loop over attributes. 
1811              par_attr_list = ['r2eff', 'i0'] 
1812   
1813              # Collect the estimation data. 
1814              my_dic = {} 
1815              param_key_list = [] 
1816              est_keys = [] 
1817              est_key = 'grid' 
1818              est_keys.append(est_key) 
1819              spin_id_list = [] 
1820   
1821              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1822                  # Add key to dic. 
1823                  my_dic[spin_id] = {} 
1824   
1825                  # Add key for estimate. 
1826                  my_dic[spin_id][est_key] = {} 
1827   
1828                  # Add spin key to list. 
1829                  spin_id_list.append(spin_id) 
1830   
1831                  # Generate spin string. 
1832                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1833   
1834                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1835                      # Generate the param_key. 
1836                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1837                      #param_key = generate_r20_key(exp_type=exp_type, frq=frq) 
1838   
1839                      # Append key. 
1840                      param_key_list.append(param_key) 
1841   
1842                      # Add key to dic. 
1843                      my_dic[spin_id][est_key][param_key] = {} 
1844   
1845                      # Get the value. 
1846                      # Loop over err attributes. 
1847                      for par_attr in par_attr_list: 
1848                          if hasattr(cur_spin, par_attr): 
1849                              get_par_attr = getattr(cur_spin, par_attr)[param_key] 
1850                          else: 
1851                              get_par_attr = 0.0 
1852   
1853                          # Save to dic. 
1854                          my_dic[spin_id][est_key][param_key][par_attr] = get_par_attr 
1855   
1856                      # Check number of values. 
1857                      values = [] 
1858                      errors = [] 
1859                      times = [] 
1860                      for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1861                          value = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, sim_index=None) 
1862                          values.append(value) 
1863   
1864                          error = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True) 
1865                          errors.append(error) 
1866                          times.append(time) 
1867   
1868                      # Save to dic. 
1869                      my_dic[spin_id][est_key][param_key]['values'] = values 
1870                      my_dic[spin_id][est_key][param_key]['errors'] = errors 
1871                      my_dic[spin_id][est_key][param_key]['times'] = times 
1872   
1873          # Analysis variables. 
1874          ##################### 
1875   
1876          # The dispersion models. 
1877          MODELS = ['R2eff', 'No Rex'] 
1878   
1879          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
1880          MC_NUM = 10 
1881   
1882          # A flag which if True will activate Monte Carlo simulations for all models.  Note this will hugely increase the computation time. 
1883          MC_SIM_ALL_MODELS = False 
1884   
1885          # The results directory. 
1886          RESULTS_DIR = ds.tmpdir 
1887   
1888          # The directory of results of an earlier analysis without clustering. 
1889          PRE_RUN_DIR = None 
1890   
1891          # The model selection technique to use. 
1892          MODSEL = 'AIC' 
1893   
1894          # The flag for only using numeric models in the final model selection. 
1895          NUMERIC_ONLY = False 
1896   
1897          # The R1rho value in rad/s by which to judge insignificance.  If the maximum difference between two points on all dispersion curves for a spin is less than this value, that spin will be deselected. 
1898          INSIGNIFICANCE = 1.0 
1899   
1900          # Auto-analysis execution. 
1901          self.assertRaises(RelaxError, relax_disp.Relax_disp, pipe_name='relax_disp', results_dir=RESULTS_DIR, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, insignificance=INSIGNIFICANCE, numeric_only=NUMERIC_ONLY) 
1902   
1903   
1904 -    def test_bug_negative_intensities_cpmg(self): 
1905          """Test data, where peak intensities are negative in CPMG 
1906   
1907          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
1908          """ 
1909   
1910          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+'bug_neg_int_acbp_cpmg_disp_048MGuHCl_40C_041223' 
1911   
1912          # Create the spins 
1913          self.interpreter.spectrum.read_spins(file="peaks_list_max_standard.ser", dir=data_path) 
1914   
1915          # Name the isotope for field strength scaling. 
1916          self.interpreter.spin.isotope(isotope='15N') 
1917   
1918          # Read the spectrum from NMRSeriesTab file. The "auto" will generate spectrum name of form: Z_A{i} 
1919          self.interpreter.spectrum.read_intensities(file="peaks_list_max_standard.ser", dir=data_path, spectrum_id='auto', int_method='height') 
1920   
1921          # Loop over the spectra settings. 
1922          ncycfile=open(data_path + sep + 'ncyc.txt', 'r') 
1923   
1924          # Make empty ncyclist 
1925          ncyclist = [] 
1926   
1927          i = 0 
1928          for line in ncycfile: 
1929              ncyc = line.split()[0] 
1930              time_T2 = float(line.split()[1]) 
1931              vcpmg = line.split()[2] 
1932              set_sfrq = float(line.split()[3]) 
1933              rmsd_err = float(line.split()[4]) 
1934   
1935              # Test if spectrum is a reference 
1936              if float(vcpmg) == 0.0: 
1937                  vcpmg = None 
1938              else: 
1939                  vcpmg = round(float(vcpmg), 3) 
1940   
1941              # Add ncyc to list 
1942              ncyclist.append(int(ncyc)) 
1943   
1944              # Set the current spectrum id 
1945              current_id = "Z_A%s"%(i) 
1946   
1947              # Set the current experiment type. 
1948              self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 
1949   
1950              # Set the peak intensity errors, as defined as the baseplane RMSD. 
1951              self.interpreter.spectrum.baseplane_rmsd(error=rmsd_err, spectrum_id=current_id) 
1952   
1953              # Set the NMR field strength of the spectrum. 
1954              self.interpreter.spectrometer.frequency(id=current_id, frq=set_sfrq, units='MHz') 
1955   
1956              # Relaxation dispersion CPMG constant time delay T (in s). 
1957              self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 
1958   
1959              # Set the relaxation dispersion CPMG frequencies. 
1960              self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 
1961   
1962              i += 1 
1963   
1964          # Specify the duplicated spectra. 
1965          self.interpreter.spectrum.replicated(spectrum_ids=['Z_A1', 'Z_A15']) 
1966   
1967          # Delete replicate spectrum 
1968          #self.interpreter.spectrum.delete('Z_A15') 
1969   
1970          MODELS = [MODEL_R2EFF, MODEL_NOREX] 
1971          GRID_INC = 5; MC_NUM = 3; MODSEL = 'AIC' 
1972   
1973          results_dir = ds.tmpdir 
1974   
1975          # Execute 
1976          relax_disp.Relax_disp(pipe_name='relax_disp', results_dir=results_dir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
1977   
1978          # Check spin less R2eff points. 
1979          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
1980              # Assert that spin 4, has one less R2eff point, since one of the intensities are negative. 
1981              if spin_id == ':4@N': 
1982                  self.assertEqual(len(cur_spin.r2eff), 14) 
1983              else: 
1984                  self.assertEqual(len(cur_spin.r2eff), 15) 
1985   
1986   
1987 -    def test_check_missing_r1(self): 
1988          """Test of the check_missing_r1() function.""" 
1989   
1990          # Set up some spins. 
1991          self.setup_missing_r1_spins() 
1992   
1993          # Set variables. 
1994          exp_type = 'R1rho' 
1995          frq = 800.1 * 1E6 
1996   
1997          spectrum_id='test' 
1998   
1999          # Set an experiment type to the pipe. 
2000          self.interpreter.relax_disp.exp_type(spectrum_id=spectrum_id, exp_type=exp_type) 
2001   
2002          # Set a frequency to loop through. 
2003          self.interpreter.spectrometer.frequency(id=spectrum_id, frq=frq, units='Hz') 
2004   
2005          # Check R1 for DPL94. 
2006          check_missing_r1_return = check_missing_r1(model=MODEL_DPL94) 
2007          self.assertEqual(check_missing_r1_return, True) 
2008   
2009          # Check R1 for R2eff. 
2010          check_missing_r1_return = check_missing_r1(model=MODEL_R2EFF) 
2011          self.assertEqual(check_missing_r1_return, False) 
2012   
2013          # The path to the data files. 
2014          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
2015   
2016          # Now load some R1 data. 
2017          self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
2018   
2019          # Check R1. 
2020          check_missing_r1_return = check_missing_r1(model=MODEL_DPL94) 
2021          self.assertEqual(check_missing_r1_return, False) 
2022   
2023   
2024 -    def test_cpmg_synthetic_b14_to_ns3d_cluster(self): 
2025          """Test synthetic cpmg data.  Created with B14, analysed with NS CPMG 2site 3D, for clustered analysis. 
2026   
2027          This is part of: U{Task #7807 <https://gna.org/task/index.php?7807>}: Speed-up of dispersion models for Clustered analysis. 
2028   
2029          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2030          """ 
2031   
2032          # Reset. 
2033          #self.interpreter.reset() 
2034   
2035          ## Set Experiments. 
2036          model_create = 'B14' 
2037          #model_create = 'NS CPMG 2-site expanded' 
2038          model_analyse = 'NS CPMG 2-site 3D' 
2039   
2040          # Exp 1 
2041          sfrq_1 = 599.8908617*1E6 
2042          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2043          time_T2_1 = 0.06 
2044          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2045          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2046          r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2047          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2048   
2049          sfrq_2 = 499.8908617*1E6 
2050          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2051          time_T2_2 = 0.05 
2052          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2053          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2054          r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2055          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2056   
2057          # Collect all exps 
2058          exps = [exp_1, exp_2] 
2059   
2060          spins = [ 
2061              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.95, 'dw': 2.} ], 
2062              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.95, 'dw': 1.} ] 
2063              ] 
2064   
2065          # Collect the data to be used. 
2066          ds.data = [model_create, model_analyse, spins, exps] 
2067   
2068          # The tmp directory. None is the local directory. 
2069          ds.tmpdir = ds.tmpdir 
2070   
2071          # The results directory. None is the local directory. 
2072          #ds.resdir = None 
2073          ds.resdir = ds.tmpdir 
2074   
2075          # Do r20_from_min_r2eff ?. 
2076          ds.r20_from_min_r2eff = True 
2077   
2078          # Remove insignificant level. 
2079          ds.insignificance = 0.0 
2080   
2081          # The grid search size (the number of increments per dimension). 
2082          ds.GRID_INC = None 
2083   
2084          # The do clustering. 
2085          ds.do_cluster = True 
2086   
2087          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2088          # The default value is 1e-25. 
2089          ds.set_func_tol = 1e-1 
2090   
2091          # The maximum number of iterations. 
2092          # The default value is 1e7. 
2093          ds.set_max_iter = 1000 
2094   
2095          # The verbosity level. 
2096          ds.verbosity = 1 
2097   
2098          # The rel_change WARNING level. 
2099          ds.rel_change = 0.05 
2100   
2101          # The plot_curves. 
2102          ds.plot_curves = False 
2103   
2104          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2105          ds.sherekhan_input = False 
2106   
2107          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2108          ds.opendx = False 
2109   
2110          # The set r2eff err. 
2111          ds.r2eff_err = 0.1 
2112   
2113          # The print result info. 
2114          ds.print_res = True 
2115   
2116          # Execute the script. 
2117          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2118   
2119          cur_spins = ds.data[2] 
2120          # Compare results. 
2121          for i in range(len(cur_spins)): 
2122              res_name, res_num, spin_name, params = cur_spins[i] 
2123              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2124              cur_spin = return_spin(cur_spin_id) 
2125   
2126              grid_params = ds.grid_results[i][3] 
2127   
2128              # Extract the clust results. 
2129              min_params = ds.clust_results[i][3] 
2130              # Now read the parameters. 
2131              print("For spin: '%s'"%cur_spin_id) 
2132              for mo_param in cur_spin.params: 
2133                  # The R2 is a dictionary, depending on spectrometer frequency. 
2134                  if isinstance(getattr(cur_spin, mo_param), dict): 
2135                      grid_r2 = grid_params[mo_param] 
2136                      min_r2 = min_params[mo_param] 
2137                      set_r2 = params[mo_param] 
2138                      for key, val in list(set_r2.items()): 
2139                          grid_r2_frq = grid_r2[key] 
2140                          min_r2_frq = min_r2[key] 
2141                          set_r2_frq = set_r2[key] 
2142                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2143                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2144                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2145                          if rel_change > ds.rel_change: 
2146                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2147                              print("###################################") 
2148   
2149                          ## Make test on R2. 
2150                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2151                  else: 
2152                      grid_val = grid_params[mo_param] 
2153                      min_val = min_params[mo_param] 
2154                      set_val = params[mo_param] 
2155                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2156                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2157                      if rel_change > ds.rel_change: 
2158                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2159                          print("###################################") 
2160   
2161                      ## Make test on parameters. 
2162                      if mo_param == 'dw': 
2163                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2164                      elif mo_param == 'kex': 
2165                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2166                      elif mo_param == 'pA': 
2167                          self.assertAlmostEqual(set_val, min_val, 2) 
2168   
2169   
2170 -    def test_cpmg_synthetic_b14_to_ns_star_cluster(self): 
2171          """Test synthetic cpmg data.  Created with B14, analysed with NS CPMG 2site STAR, for clustered analysis. 
2172   
2173          This is part of: U{Task #7807 <https://gna.org/task/index.php?7807>}: Speed-up of dispersion models for Clustered analysis. 
2174   
2175          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2176          """ 
2177   
2178          # Reset. 
2179          #self.interpreter.reset() 
2180   
2181          ## Set Experiments. 
2182          model_create = 'B14' 
2183          #model_create = 'NS CPMG 2-site expanded' 
2184          model_analyse = 'NS CPMG 2-site star' 
2185   
2186          # Exp 1 
2187          sfrq_1 = 599.8908617*1E6 
2188          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2189          time_T2_1 = 0.06 
2190          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2191          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2192          r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2193          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2194   
2195          sfrq_2 = 499.8908617*1E6 
2196          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2197          time_T2_2 = 0.05 
2198          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2199          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2200          r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2201          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2202   
2203          # Collect all exps 
2204          exps = [exp_1, exp_2] 
2205   
2206          spins = [ 
2207              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.95, 'dw': 2.} ], 
2208              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.95, 'dw': 1.} ] 
2209              ] 
2210   
2211          # Collect the data to be used. 
2212          ds.data = [model_create, model_analyse, spins, exps] 
2213   
2214          # The tmp directory. None is the local directory. 
2215          ds.tmpdir = ds.tmpdir 
2216   
2217          # The results directory. None is the local directory. 
2218          #ds.resdir = None 
2219          ds.resdir = ds.tmpdir 
2220   
2221          # Do r20_from_min_r2eff ?. 
2222          ds.r20_from_min_r2eff = True 
2223   
2224          # Remove insignificant level. 
2225          ds.insignificance = 0.0 
2226   
2227          # The grid search size (the number of increments per dimension). 
2228          ds.GRID_INC = None 
2229   
2230          # The do clustering. 
2231          ds.do_cluster = True 
2232   
2233          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2234          # The default value is 1e-25. 
2235          ds.set_func_tol = 1e-1 
2236   
2237          # The maximum number of iterations. 
2238          # The default value is 1e7. 
2239          ds.set_max_iter = 1000 
2240   
2241          # The verbosity level. 
2242          ds.verbosity = 1 
2243   
2244          # The rel_change WARNING level. 
2245          ds.rel_change = 0.05 
2246   
2247          # The plot_curves. 
2248          ds.plot_curves = False 
2249   
2250          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2251          ds.sherekhan_input = False 
2252   
2253          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2254          ds.opendx = False 
2255   
2256          # The set r2eff err. 
2257          ds.r2eff_err = 0.1 
2258   
2259          # The print result info. 
2260          ds.print_res = True 
2261   
2262          # Execute the script. 
2263          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2264   
2265          cur_spins = ds.data[2] 
2266          # Compare results. 
2267          for i in range(len(cur_spins)): 
2268              res_name, res_num, spin_name, params = cur_spins[i] 
2269              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2270              cur_spin = return_spin(cur_spin_id) 
2271   
2272              grid_params = ds.grid_results[i][3] 
2273   
2274              # Extract the clust results. 
2275              min_params = ds.clust_results[i][3] 
2276              # Now read the parameters. 
2277              print("For spin: '%s'"%cur_spin_id) 
2278              for mo_param in cur_spin.params: 
2279                  # The R2 is a dictionary, depending on spectrometer frequency. 
2280                  if isinstance(getattr(cur_spin, mo_param), dict): 
2281                      grid_r2 = grid_params[mo_param] 
2282                      min_r2 = min_params[mo_param] 
2283                      set_r2 = params[mo_param] 
2284                      for key, val in list(set_r2.items()): 
2285                          grid_r2_frq = grid_r2[key] 
2286                          min_r2_frq = min_r2[key] 
2287                          set_r2_frq = set_r2[key] 
2288                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2289                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2290                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2291                          if rel_change > ds.rel_change: 
2292                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2293                              print("###################################") 
2294   
2295                          ## Make test on R2. 
2296                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2297                  else: 
2298                      grid_val = grid_params[mo_param] 
2299                      min_val = min_params[mo_param] 
2300                      set_val = params[mo_param] 
2301                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2302                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2303                      if rel_change > ds.rel_change: 
2304                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2305                          print("###################################") 
2306   
2307                      ## Make test on parameters. 
2308                      if mo_param == 'dw': 
2309                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2310                      elif mo_param == 'kex': 
2311                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2312                      elif mo_param == 'pA': 
2313                          self.assertAlmostEqual(set_val, min_val, 2) 
2314   
2315   
2316 -    def test_cpmg_synthetic_ns3d_to_cr72(self): 
2317          """Test synthetic cpmg data. 
2318   
2319          This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with CR72. 
2320          """ 
2321   
2322          # Reset. 
2323          #self.interpreter.reset() 
2324   
2325          ## Set Experiments. 
2326          model_create = 'NS CPMG 2-site 3D' 
2327          #model_create = 'NS CPMG 2-site expanded' 
2328          model_analyse = 'CR72' 
2329          # Exp 1 
2330          sfrq_1 = 599.8908617*1E6 
2331          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2332          time_T2_1 = 0.06 
2333          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2334          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2335          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2336   
2337          sfrq_2 = 499.8908617*1E6 
2338          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2339          time_T2_2 = 0.05 
2340          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2341          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2342          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2343   
2344          # Collect all exps 
2345          exps = [exp_1, exp_2] 
2346   
2347          spins = [ 
2348              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 
2349              ] 
2350   
2351          # Collect the data to be used. 
2352          ds.data = [model_create, model_analyse, spins, exps] 
2353   
2354          # The tmp directory. None is the local directory. 
2355          ds.tmpdir = ds.tmpdir 
2356   
2357          # The results directory. None is the local directory. 
2358          #ds.resdir = None 
2359          ds.resdir = ds.tmpdir 
2360   
2361          # Do r20_from_min_r2eff ?. 
2362          ds.r20_from_min_r2eff = True 
2363   
2364          # Remove insignificant level. 
2365          ds.insignificance = 0.0 
2366   
2367          # The grid search size (the number of increments per dimension). 
2368          ds.GRID_INC = 8 
2369   
2370          # The do clustering. 
2371          ds.do_cluster = False 
2372   
2373          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2374          # The default value is 1e-25. 
2375          ds.set_func_tol = 1e-9 
2376   
2377          # The maximum number of iterations. 
2378          # The default value is 1e7. 
2379          ds.set_max_iter = 1000 
2380   
2381          # The verbosity level. 
2382          ds.verbosity = 1 
2383   
2384          # The rel_change WARNING level. 
2385          ds.rel_change = 0.05 
2386   
2387          # The plot_curves. 
2388          ds.plot_curves = False 
2389   
2390          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2391          ds.sherekhan_input = False 
2392   
2393          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2394          ds.opendx = False 
2395   
2396          # The set r2eff err. 
2397          ds.r2eff_err = 0.1 
2398   
2399          # The print result info. 
2400          ds.print_res = False 
2401   
2402          # Execute the script. 
2403          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2404   
2405          cur_spins = ds.data[2] 
2406          # Compare results. 
2407          for i in range(len(cur_spins)): 
2408              res_name, res_num, spin_name, params = cur_spins[i] 
2409              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2410              cur_spin = return_spin(cur_spin_id) 
2411   
2412              grid_params = ds.grid_results[i][3] 
2413              min_params = ds.min_results[i][3] 
2414              # Now read the parameters. 
2415              print("For spin: '%s'"%cur_spin_id) 
2416              for mo_param in cur_spin.params: 
2417                  # The R2 is a dictionary, depending on spectrometer frequency. 
2418                  if isinstance(getattr(cur_spin, mo_param), dict): 
2419                      grid_r2 = grid_params[mo_param] 
2420                      min_r2 = min_params[mo_param] 
2421                      set_r2 = params[mo_param] 
2422                      for key, val in list(set_r2.items()): 
2423                          grid_r2_frq = grid_r2[key] 
2424                          min_r2_frq = min_r2[key] 
2425                          set_r2_frq = set_r2[key] 
2426                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2427                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2428                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2429                          if rel_change > ds.rel_change: 
2430                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2431                              print("###################################") 
2432   
2433                          ## Make test on R2. 
2434                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 
2435                  else: 
2436                      grid_val = grid_params[mo_param] 
2437                      min_val = min_params[mo_param] 
2438                      set_val = params[mo_param] 
2439                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2440                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2441                      if rel_change > ds.rel_change: 
2442                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2443                          print("###################################") 
2444   
2445                      ## Make test on parameters. 
2446                      if mo_param == 'dw': 
2447                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2448                      elif mo_param == 'kex': 
2449                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2450                      elif mo_param == 'pA': 
2451                          self.assertAlmostEqual(set_val, min_val, 3) 
2452   
2453   
2454 -    def test_cpmg_synthetic_ns3d_to_b14(self): 
2455          """Test synthetic cpmg data. 
2456   
2457          This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with B14. 
2458          Try to catch bug #22021 U{https://gna.org/bugs/index.php?22021}: Model B14 shows bad fitting to data. 
2459          """ 
2460   
2461          # Reset. 
2462          #self.interpreter.reset() 
2463   
2464          ## Set Experiments. 
2465          model_create = 'NS CPMG 2-site 3D' 
2466          #model_create = 'NS CPMG 2-site expanded' 
2467          model_analyse = 'B14' 
2468          # Exp 1 
2469          sfrq_1 = 599.8908617*1E6 
2470          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2471          time_T2_1 = 0.06 
2472          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2473          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2474          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2475   
2476          sfrq_2 = 499.8908617*1E6 
2477          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2478          time_T2_2 = 0.05 
2479          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2480          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2481          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2482   
2483          # Collect all exps 
2484          exps = [exp_1, exp_2] 
2485   
2486          spins = [ 
2487              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 
2488              ] 
2489   
2490          # Collect the data to be used. 
2491          ds.data = [model_create, model_analyse, spins, exps] 
2492   
2493          # The tmp directory. None is the local directory. 
2494          ds.tmpdir = ds.tmpdir 
2495   
2496          # The results directory. None is the local directory. 
2497          #ds.resdir = None 
2498          ds.resdir = ds.tmpdir 
2499   
2500          # Do r20_from_min_r2eff ?. 
2501          ds.r20_from_min_r2eff = True 
2502   
2503          # Remove insignificant level. 
2504          ds.insignificance = 0.0 
2505   
2506          # The grid search size (the number of increments per dimension). 
2507          ds.GRID_INC = 8 
2508   
2509          # The do clustering. 
2510          ds.do_cluster = False 
2511   
2512          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2513          # The default value is 1e-25. 
2514          ds.set_func_tol = 1e-9 
2515   
2516          # The maximum number of iterations. 
2517          # The default value is 1e7. 
2518          ds.set_max_iter = 1000 
2519   
2520          # The verbosity level. 
2521          ds.verbosity = 1 
2522   
2523          # The rel_change WARNING level. 
2524          ds.rel_change = 0.05 
2525   
2526          # The plot_curves. 
2527          ds.plot_curves = False 
2528   
2529          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2530          ds.sherekhan_input = False 
2531   
2532          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2533          ds.opendx = False 
2534   
2535          # The set r2eff err. 
2536          ds.r2eff_err = 0.1 
2537   
2538          # The print result info. 
2539          ds.print_res = False 
2540   
2541          # Execute the script. 
2542          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2543   
2544          cur_spins = ds.data[2] 
2545          # Compare results. 
2546          for i in range(len(cur_spins)): 
2547              res_name, res_num, spin_name, params = cur_spins[i] 
2548              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2549              cur_spin = return_spin(cur_spin_id) 
2550   
2551              grid_params = ds.grid_results[i][3] 
2552              min_params = ds.min_results[i][3] 
2553              # Now read the parameters. 
2554              print("For spin: '%s'"%cur_spin_id) 
2555              for mo_param in cur_spin.params: 
2556                  # The R2 is a dictionary, depending on spectrometer frequency. 
2557                  if isinstance(getattr(cur_spin, mo_param), dict): 
2558                      grid_r2 = grid_params[mo_param] 
2559                      min_r2 = min_params[mo_param] 
2560                      set_r2 = params[mo_param] 
2561                      for key, val in list(set_r2.items()): 
2562                          grid_r2_frq = grid_r2[key] 
2563                          min_r2_frq = min_r2[key] 
2564                          set_r2_frq = set_r2[key] 
2565                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2566                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2567                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2568                          if rel_change > ds.rel_change: 
2569                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2570                              print("###################################") 
2571   
2572                          ## Make test on R2. 
2573                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 
2574                  else: 
2575                      grid_val = grid_params[mo_param] 
2576                      min_val = min_params[mo_param] 
2577                      set_val = params[mo_param] 
2578                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2579                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2580                      if rel_change > ds.rel_change: 
2581                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2582                          print("###################################") 
2583   
2584                      ## Make test on parameters. 
2585                      if mo_param == 'dw': 
2586                          self.assertAlmostEqual(set_val/10, min_val/10, 5) 
2587                      elif mo_param == 'kex': 
2588                          self.assertAlmostEqual(set_val/1000, min_val/1000, 5) 
2589                      elif mo_param == 'pA': 
2590                          self.assertAlmostEqual(set_val, min_val, 6) 
2591   
2592   
2593 -    def test_cpmg_synthetic_ns3d_to_cr72_noise_cluster(self): 
2594          """Test synthetic cpmg data. For CR72 with small noise and cluster. 
2595   
2596          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2597          """ 
2598   
2599          # Reset. 
2600          #self.interpreter.reset() 
2601   
2602          ## Set Experiments. 
2603          model_create = 'NS CPMG 2-site 3D' 
2604          #model_create = 'NS CPMG 2-site expanded' 
2605          model_analyse = 'CR72' 
2606   
2607          # Exp 1 
2608          sfrq_1 = 599.8908617*1E6 
2609          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2610          time_T2_1 = 0.06 
2611          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2612          r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2613          #r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2614          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2615   
2616          sfrq_2 = 499.8908617*1E6 
2617          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2618          time_T2_2 = 0.05 
2619          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2620          r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2621          #r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2622          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2623   
2624          # Collect all exps 
2625          exps = [exp_1, exp_2] 
2626   
2627          spins = [ 
2628              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ], 
2629              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.99, 'dw': 1.} ] 
2630              ] 
2631   
2632          # Collect the data to be used. 
2633          ds.data = [model_create, model_analyse, spins, exps] 
2634   
2635          # The tmp directory. None is the local directory. 
2636          ds.tmpdir = ds.tmpdir 
2637   
2638          # The results directory. None is the local directory. 
2639          #ds.resdir = None 
2640          ds.resdir = ds.tmpdir 
2641   
2642          # Do r20_from_min_r2eff ?. 
2643          ds.r20_from_min_r2eff = True 
2644   
2645          # Remove insignificant level. 
2646          ds.insignificance = 0.0 
2647   
2648          # The grid search size (the number of increments per dimension). 
2649          ds.GRID_INC = 13 
2650   
2651          # The do clustering. 
2652          ds.do_cluster = True 
2653   
2654          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2655          # The default value is 1e-25. 
2656          ds.set_func_tol = 1e-8 
2657   
2658          # The maximum number of iterations. 
2659          # The default value is 1e7. 
2660          ds.set_max_iter = 10000 
2661   
2662          # The verbosity level. 
2663          ds.verbosity = 1 
2664   
2665          # The rel_change WARNING level. 
2666          ds.rel_change = 0.05 
2667   
2668          # The plot_curves. 
2669          ds.plot_curves = False 
2670   
2671          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2672          ds.sherekhan_input = False 
2673   
2674          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2675          ds.opendx = False 
2676   
2677          # The set r2eff err. 
2678          ds.r2eff_err = 0.1 
2679   
2680          # The print result info. 
2681          ds.print_res = False 
2682   
2683          # Execute the script. 
2684          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2685   
2686          cur_spins = ds.data[2] 
2687          # Compare results. 
2688          for i in range(len(cur_spins)): 
2689              res_name, res_num, spin_name, params = cur_spins[i] 
2690              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2691              cur_spin = return_spin(cur_spin_id) 
2692   
2693              grid_params = ds.grid_results[i][3] 
2694   
2695              # Extract the clust results. 
2696              min_params = ds.clust_results[i][3] 
2697              # Now read the parameters. 
2698              print("For spin: '%s'"%cur_spin_id) 
2699              for mo_param in cur_spin.params: 
2700                  # The R2 is a dictionary, depending on spectrometer frequency. 
2701                  if isinstance(getattr(cur_spin, mo_param), dict): 
2702                      grid_r2 = grid_params[mo_param] 
2703                      min_r2 = min_params[mo_param] 
2704                      set_r2 = params[mo_param] 
2705                      for key, val in list(set_r2.items()): 
2706                          grid_r2_frq = grid_r2[key] 
2707                          min_r2_frq = min_r2[key] 
2708                          set_r2_frq = set_r2[key] 
2709                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2710                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2711                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2712                          if rel_change > ds.rel_change: 
2713                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2714                              print("###################################") 
2715   
2716                          ## Make test on R2. 
2717                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2718                  else: 
2719                      grid_val = grid_params[mo_param] 
2720                      min_val = min_params[mo_param] 
2721                      set_val = params[mo_param] 
2722                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2723                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2724                      if rel_change > ds.rel_change: 
2725                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2726                          print("###################################") 
2727   
2728                      ## Make test on parameters. 
2729                      if mo_param == 'dw': 
2730                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2731                      elif mo_param == 'kex': 
2732                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2733                      elif mo_param == 'pA': 
2734                          self.assertAlmostEqual(set_val, min_val, 2) 
2735   
2736   
2737 -    def test_cpmg_synthetic_dx_map_points(self): 
2738          """Test synthetic cpmg data, calling the dx.map function with one or two points. 
2739   
2740          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2741          """ 
2742   
2743          # Reset. 
2744          #self.interpreter.reset() 
2745   
2746          ## Set Experiments. 
2747          model_create = MODEL_NS_CPMG_2SITE_EXPANDED 
2748          model_analyse = 'CR72' 
2749          # Exp 1 
2750          sfrq_1 = 599.8908617*1E6 
2751          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2752          time_T2_1 = 0.06 
2753          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2754          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2755          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2756   
2757          sfrq_2 = 499.8908617*1E6 
2758          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2759          time_T2_2 = 0.05 
2760          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2761          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2762          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2763   
2764          # Collect all exps 
2765          exps = [exp_1, exp_2] 
2766   
2767          spins = [ 
2768              ['Ala', 1, 'N', {'r2': {r20_key_1:2, r20_key_2:2}, 'r2a': {r20_key_1:2, r20_key_2:2}, 'r2b': {r20_key_1:2, r20_key_2:2}, 'kex': 1000, 'pA': 0.99, 'dw': 2} ] 
2769              ] 
2770   
2771          # Collect the data to be used. 
2772          ds.data = [model_create, model_analyse, spins, exps] 
2773   
2774          # The tmp directory. None is the local directory. 
2775          ds.tmpdir = ds.tmpdir 
2776   
2777          # The results directory. None is the local directory. 
2778          #ds.resdir = None 
2779          ds.resdir = ds.tmpdir 
2780   
2781          # Do r20_from_min_r2eff ?. 
2782          ds.r20_from_min_r2eff = True 
2783   
2784          # Remove insignificant level. 
2785          ds.insignificance = 0.0 
2786   
2787          # The grid search size (the number of increments per dimension). 
2788          ds.GRID_INC = None 
2789   
2790          # The do clustering. 
2791          ds.do_cluster = False 
2792   
2793          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2794          # The default value is 1e-25. 
2795          ds.set_func_tol = 1e-9 
2796   
2797          # The maximum number of iterations. 
2798          # The default value is 1e7. 
2799          ds.set_max_iter = 1000 
2800   
2801          # The verbosity level. 
2802          ds.verbosity = 1 
2803   
2804          # The rel_change WARNING level. 
2805          ds.rel_change = 0.05 
2806   
2807          # The plot_curves. 
2808          ds.plot_curves = False 
2809   
2810          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2811          ds.sherekhan_input = False 
2812   
2813          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2814          ds.opendx = False 
2815   
2816          # The set r2eff err. 
2817          ds.r2eff_err = 0.1 
2818   
2819          # The print result info. 
2820          ds.print_res = False 
2821   
2822          # Execute the script. 
2823          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2824   
2825          # Get the spins. 
2826          cur_spins = ds.data[2] 
2827   
2828          # First switch pipe, since dx.map will go through parameters and end up a "bad" place. :-) 
2829          ds.pipe_name_MODEL_MAP = "%s_%s_map"%(ds.pipe_name, model_analyse) 
2830          self.interpreter.pipe.copy(pipe_from=ds.pipe_name, pipe_to=ds.pipe_name_MODEL_MAP, bundle_to = ds.pipe_bundle) 
2831          self.interpreter.pipe.switch(pipe_name=ds.pipe_name_MODEL_MAP) 
2832   
2833          # Copy R2eff, but not the original parameters 
2834          self.interpreter.value.copy(pipe_from=ds.pipe_name_r2eff, pipe_to=ds.pipe_name_MODEL_MAP, param='r2eff') 
2835   
2836          # Then select model. 
2837          self.interpreter.relax_disp.select_model(model=model_analyse) 
2838   
2839          # Define dx.map settings. 
2840          ds.dx_inc = 4 
2841          ds.dx_params = ['dw', 'pA', 'kex'] 
2842   
2843          res_name, res_num, spin_name, params = cur_spins[0] 
2844          cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2845          cur_spin = return_spin(cur_spin_id) 
2846   
2847          print("Params for dx map is") 
2848          print(ds.dx_params) 
2849          print("Point param for dx map is") 
2850          print(ds.dx_set_val) 
2851          cur_model = model_analyse.replace(' ', '_') 
2852          file_name_map = "%s_map%s" % (cur_model, cur_spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
2853          file_name_point = "%s_point%s" % (cur_model, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 
2854          self.interpreter.dx.map(params=ds.dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=ds.dx_inc, lower=None, upper=None, axis_incs=10, file_prefix=file_name_map, dir=ds.resdir, point=[ds.dx_set_val, ds.dx_clust_val], point_file=file_name_point, create_par_file=True) 
2855   
2856          ## Check for file creation 
2857          # Set filepaths. 
2858          map_cfg = ds.tmpdir+sep+file_name_map+".cfg" 
2859          map_net = ds.tmpdir+sep+file_name_map+".net" 
2860          map_general = ds.tmpdir+sep+file_name_map+".general" 
2861          map_par = get_file_path(file_name=file_name_map+".par", dir=ds.tmpdir) 
2862          map_plot = get_file_path(file_name=file_name_map+".py", dir=ds.tmpdir) 
2863   
2864          point_general = ds.tmpdir+sep+file_name_point+".general" 
2865          point_point = ds.tmpdir+sep+file_name_point 
2866          point_par = get_file_path(file_name=file_name_point+".par", dir=ds.tmpdir) 
2867   
2868          # Test the files exists. 
2869          self.assert_(access(map_cfg, F_OK)) 
2870          self.assert_(access(map_net, F_OK)) 
2871          self.assert_(access(map_general, F_OK)) 
2872          self.assert_(access(map_par, F_OK)) 
2873          self.assert_(access(map_plot, F_OK)) 
2874          self.assert_(access(point_general, F_OK)) 
2875          self.assert_(access(point_point, F_OK)) 
2876          self.assert_(access(point_par, F_OK)) 
2877   
2878          # Open the files for testing. 
2879          # Check the cfg file. 
2880          print("\nChecking the dx map .cfg file.") 
2881          res_file = [ 
2882              '//'+"\n", 
2883              '//'+"\n", 
2884              '// time: Thu May  8 18:55:31 2014'+"\n", 
2885              '//'+"\n", 
2886              '// version: 3.2.0 (format), 4.3.2 (DX)'+"\n", 
2887              '//'+"\n", 
2888              '//'+"\n", 
2889              '// panel[0]: position = (0.0164,0.0000), size = 0.2521x0.1933, startup = 1, devstyle = 1'+"\n", 
2890              '// title: value = Control Panel'+"\n", 
2891              '//'+"\n", 
2892              '// workspace: width = 251, height = 142'+"\n", 
2893              '// layout: snap = 0, width = 50, height = 50, align = NN'+"\n", 
2894              '//'+"\n", 
2895              '// interactor Selector[1]: num_components = 1, value = 1 '+"\n", 
2896              '// selections: maximum = 2, current = 0 '+"\n", 
2897              '// option[0]: name = "Colour", value = 1'+"\n", 
2898              '// option[1]: name = "Grey", value = 2'+"\n", 
2899              '// instance: panel = 0, x = 81, y = 6, style = Scrolled List, vertical = 1, size = 170x136'+"\n", 
2900              '// label: value = Colour Selector'+"\n", 
2901              '//'+"\n", 
2902              '// node Image[3]:'+"\n", 
2903              '// title: value = Surface'+"\n", 
2904              '// depth: value = 24'+"\n", 
2905              '// window: position = (0.0000,0.0400), size = 0.9929x0.9276'+"\n", 
2906          ] 
2907          file = open(map_cfg, 'r') 
2908          lines = file.readlines() 
2909          file.close() 
2910          for i in range(len(res_file)): 
2911              # Skip time point 
2912              if i == 2: 
2913                  continue 
2914              self.assertEqual(res_file[i], lines[i]) 
2915   
2916          print("\nChecking the dx map .general file.") 
2917          res_file = [ 
2918              'file = CR72_map_1_N'+"\n", 
2919              'grid = 5 x 5 x 5'+"\n", 
2920              'format = ascii'+"\n", 
2921              'interleaving = field'+"\n", 
2922              'majority = row'+"\n", 
2923              'field = data'+"\n", 
2924              'structure = scalar'+"\n", 
2925              'type = float'+"\n", 
2926              'dependency = positions'+"\n", 
2927              'positions = regular, regular, regular, 0, 1, 0, 1, 0, 1'+"\n", 
2928              ''+"\n", 
2929              'end'+"\n", 
2930          ] 
2931          file = open(map_general, 'r') 
2932          lines = file.readlines() 
2933          file.close() 
2934          for i in range(len(res_file)): 
2935              # Skip time point 
2936              #if i == 2: 
2937              #    continue 
2938              self.assertEqual(res_file[i], lines[i]) 
2939   
2940          print("\nChecking the dx point .general file.") 
2941          res_file = [ 
2942              'file = CR72_point_1_N'+"\n", 
2943              'points = 2'+"\n", 
2944              'format = ascii'+"\n", 
2945              'interleaving = field'+"\n", 
2946              'field = locations, field0'+"\n", 
2947              'structure = 3-vector, scalar'+"\n", 
2948              'type = float, float'+"\n", 
2949              ''+"\n", 
2950              'end'+"\n", 
2951          ] 
2952          file = open(point_general, 'r') 
2953          lines = file.readlines() 
2954          file.close() 
2955          for i in range(len(res_file)): 
2956              # Skip time point 
2957              #if i == 2: 
2958              #    continue 
2959              self.assertEqual(res_file[i], lines[i]) 
2960   
2961          print("\nChecking the dx point point file.") 
2962          res_file = [ 
2963              '0.8            3.92           0.39964        1'+"\n", 
2964              '0.76981        3.9169         0.41353        1'+"\n", 
2965          ] 
2966          file = open(point_point, 'r') 
2967          lines = file.readlines() 
2968          file.close() 
2969          for i in range(len(res_file)): 
2970              # Skip time point 
2971              #if i == 2: 
2972              #    continue 
2973              self.assertEqual(res_file[i], lines[i]) 
2974   
2975          print("\nChecking the dx point par file.") 
2976          res_file = [ 
2977              '# i    dw         pA         kex           chi2          i_sort    dw_sort    pA_sort    kex_sort      chi2_sort     '+"\n", 
2978              '0      2.00000    0.99000    1000.00000    6185.84926    0         2.00000    0.99000    1000.00000    6185.84926    '+"\n", 
2979              '1      1.92453    0.98961    1034.72206    6396.02770    1         1.92453    0.98961    1034.72206    6396.02770    '+"\n", 
2980          ] 
2981          res_file2 = [ 
2982              '# i    dw         pA         kex           chi2          i_sort    dw_sort    pA_sort    kex_sort      chi2_sort     '+"\n", 
2983              '0      2.00000    0.99000    1000.00000    6185.84926    0         2.00000    0.99000    1000.00000    6185.84926    '+"\n", 
2984              '1      1.92452    0.98961    1034.72424    6396.02439    1         1.92452    0.98961    1034.72424    6396.02439    '+"\n", 
2985          ]  # Python 2.5 and 3.1. 
2986          file = open(point_par, 'r') 
2987          lines = file.readlines() 
2988          file.close() 
2989          for i in range(len(res_file)): 
2990              if lines[i] != res_file[i] and lines[i] != res_file2[i]: 
2991                  self.assertEqual(res_file[i], lines[i]) 
2992   
2993          print("\nChecking the matplotlib surface plot file.") 
2994          res_file = [ 
2995              'from copy import deepcopy'+"\n", 
2996              'import numpy as np'+"\n", 
2997              'import scipy.interpolate'+"\n", 
2998              'from numpy.ma import masked_where'+"\n", 
2999              ''+"\n", 
3000              'from mpl_toolkits.mplot3d import axes3d'+"\n", 
3001              'import matplotlib.pyplot as plt'+"\n", 
3002              'from matplotlib import cm'+"\n", 
3003              ''+"\n", 
3004              '# Open file and get header.'+"\n", 
3005              'mapfile_name = "%s.par"'%file_name_map+"\n", 
3006              'pointfile_name = "%s.par"'%file_name_point+"\n", 
3007              ''+"\n", 
3008          ] 
3009          file = open(map_plot, 'r') 
3010          lines = file.readlines() 
3011          file.close() 
3012          for i in range(len(res_file)): 
3013              self.assertEqual(res_file[i], lines[i]) 
3014   
3015   
3016 -    def test_curve_type_cpmg_fixed_time(self): 
3017          """Test the curve type detection using the Dr. Flemming Hansen's CPMG fixed time test data.""" 
3018   
3019          # Reset. 
3020          self.interpreter.reset() 
3021   
3022          # Load the base data. 
3023          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
3024          self.interpreter.state.load(data_path+sep+'r2eff_values') 
3025   
3026          # The type. 
3027          curve_type = get_curve_type(id='500_133.33.in') 
3028          self.assertEqual(curve_type, 'fixed time') 
3029   
3030   
3031 -    def test_curve_type_r1rho_exponential(self, model=None): 
3032          """Test the curve type detection using the 'M61' exponential test data.""" 
3033   
3034          # Reset. 
3035          self.interpreter.reset() 
3036   
3037          # Load the base data. 
3038          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_on_res_m61' 
3039          self.interpreter.state.load(data_path+sep+'r2eff_values') 
3040   
3041          # The type. 
3042          curve_type = get_curve_type(id='nu_2000_ncyc9') 
3043          self.assertEqual(curve_type, 'exponential') 
3044   
3045   
3046 -    def test_curve_type_r1rho_fixed_time(self, model=None): 
3047          """Test the curve type detection using the 'TP02' fixed time test data.""" 
3048   
3049          # Reset. 
3050          self.interpreter.reset() 
3051   
3052          # Load the base data. 
3053          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 
3054          self.interpreter.state.load(data_path+sep+'r2eff_values') 
3055   
3056          # The type. 
3057          curve_type = get_curve_type(id='nu_1000.0_500MHz') 
3058          self.assertEqual(curve_type, 'fixed time') 
3059   
3060   
3061 -    def test_dpl94_data_to_dpl94(self): 
3062          """Test the relaxation dispersion 'DPL94' model curve fitting to fixed time synthetic data.""" 
3063   
3064          # Fixed time variable. 
3065          ds.fixed = True 
3066   
3067          # Execute the script. 
3068          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_dpl94.py') 
3069   
3070          # The original parameters. 
3071          i0 = [100000.0, 20000.0] 
3072          r1rho_prime = [2.25, 24.0] 
3073          pA = 0.7 
3074          kex = 1000.0 
3075          delta_omega = [1.0, 2.0] 
3076          phi_ex = [] 
3077          for i in range(2): 
3078              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
3079   
3080          # Switch to the 'DPL94' model data pipe, then check for each spin. 
3081          self.interpreter.pipe.switch('DPL94 - relax_disp') 
3082          spin_index = 0 
3083          for spin, spin_id in spin_loop(return_id=True): 
3084              # Printout. 
3085              print("\nSpin %s." % spin_id) 
3086   
3087              # Check the fitted parameters. 
3088              self.assertAlmostEqual(spin.r2['R1rho - 800.00000000 MHz']/10, r1rho_prime[spin_index]/10, 2) 
3089              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
3090              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
3091   
3092              # Increment the spin index. 
3093              spin_index += 1 
3094   
3095   
3096 -    def test_dx_map_clustered(self): 
3097          """Test making dx_map for residues under clustered calculation. 
3098   
3099          This uses CPMG data from: 
3100              - Webb H, Tynan-Connolly BM, Lee GM, Farrell D, O'Meara F, Soendergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE 
3101                Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. 
3102                (2011), Proteins: Struct, Funct, Bioinf 79(3):685-702, U{DOI 10.1002/prot.22886<http://dx.doi.org/10.1002/prot.22886>} 
3103          """ 
3104   
3105          # Define path to data  
3106          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'HWebb_KTeilum_Proteins_Struct_Funct_Bioinf_2011' 
3107   
3108          # Read data. 
3109          self.interpreter.results.read(prev_data_path + sep + 'FT_-_CR72_-_min_-_128_-_free_spins') 
3110   
3111          # Get residue of interest. 
3112          cur_spin_id = ":%i@%s"%(52, 'N') 
3113          cur_spin_id_str = cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_') 
3114   
3115          # Get the spin container. 
3116          cur_spin = return_spin(cur_spin_id) 
3117   
3118          # Get the chi2 value 
3119          pre_chi2 = cur_spin.chi2 
3120   
3121          # Then do a local minimisation. 
3122          #self.interpreter.select.spin(":%i@%s"%(2, 'N')) 
3123          self.interpreter.minimise.calculate() 
3124   
3125          # Get the chi2 value after calculation. 
3126          calc_chi2 = cur_spin.chi2 
3127   
3128          # Assert calculation is equal. 
3129          self.assertAlmostEqual(pre_chi2, calc_chi2) 
3130   
3131          # Define dx.map settings. 
3132          dx_inc = 2 
3133          dx_inc_sides = dx_inc / 2 
3134   
3135          dx_params = ['dw', 'pA', 'kex'] 
3136          dx_point_clustered_min = [cur_spin.dw, cur_spin.pA, cur_spin.kex] 
3137   
3138          print("Params for dx map is") 
3139          print(dx_params) 
3140          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3141          print(dx_point_clustered_min) 
3142   
3143          # Define file_names. 
3144          cur_model = 'CR72' 
3145          file_name_map = "%s_map%s" % (cur_model, cur_spin_id_str) 
3146          file_name_point = "%s_point%s" % (cur_model, cur_spin_id_str) 
3147   
3148          # Step-size of parameter is 10 % 
3149          param_delta = 0.1 
3150   
3151          # Determine bounds for lower and upper 
3152          lower = [] 
3153          upper = [] 
3154          for i, param_val in enumerate(dx_point_clustered_min): 
3155              param = dx_params[i] 
3156              step_val = param_delta * param_val 
3157              step_length = step_val * dx_inc_sides 
3158   
3159              # Calculate value 
3160              low_val = param_val - step_length 
3161              lower.append(low_val) 
3162   
3163              upp_val = param_val + step_length 
3164              upper.append(upp_val) 
3165   
3166              print("For param %s, lower=%3.3f, upper=%3.3f, step_value=%3.3f, steps=%i, centered at=%3.3f"% (param, low_val, upp_val, step_val, dx_inc, param_val)) 
3167   
3168          # If the number of increments are 2, there will be 3 point calculations per parameter. 
3169          # Since we have ordered the lower and upper limits on sides of the parameter, the middle index should give us the expected global value. 
3170          dx_param_indexes = dx_inc + 1 
3171          dx_point_index = dx_inc_sides + 1 
3172   
3173          # Find the line number. 
3174          line = 1 
3175          for i in range(1, dx_param_indexes + 1): 
3176              for j in range(1, dx_param_indexes + 1): 
3177                  for k in range(1, dx_param_indexes + 1): 
3178                      if i == dx_point_index and j == dx_point_index and k == dx_point_index: 
3179                          line_chi2 = line 
3180                      # Add to line counter. 
3181                      line += 1 
3182   
3183          # Define temporary folder. 
3184          result_dir = self.tmpdir 
3185   
3186          # For testing. 
3187          #result_dir = None 
3188          #lower = None 
3189          #upper = None 
3190          #self.interpreter.relax_disp.cluster(cluster_id='free spins', spin_id=cur_spin_id) 
3191   
3192   
3193          # Then do the map. 
3194          self.interpreter.dx.map(params=dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=dx_inc, lower=lower, upper=upper, axis_incs=10, file_prefix=file_name_map, dir=result_dir, point=dx_point_clustered_min, point_file=file_name_point) 
3195   
3196          # Print where to locate values. 
3197          nr_chi2_val = dx_param_indexes**3 
3198          print("Nr of chi2 calculations are=%i"%nr_chi2_val) 
3199          print("Global chi2=%3.3f, Calc_chi=%3.3f, map_line_chi2=%i" % (pre_chi2, calc_chi2, line_chi2) ) 
3200   
3201          ## Check for file creation 
3202          # Set filepaths. 
3203          map_name = get_file_path(file_name=file_name_map, dir=result_dir) 
3204          map_cfg = get_file_path(file_name=file_name_map+".cfg", dir=result_dir) 
3205          map_net = get_file_path(file_name=file_name_map+".net", dir=result_dir) 
3206          map_general = get_file_path(file_name=file_name_map+".general", dir=result_dir) 
3207   
3208          point_general = get_file_path(file_name=file_name_point+".general", dir=result_dir) 
3209          point_point = get_file_path(file_name=file_name_point, dir=result_dir) 
3210   
3211          # Test the files exists. 
3212          self.assert_(access(map_cfg, F_OK)) 
3213          self.assert_(access(map_net, F_OK)) 
3214          self.assert_(access(map_general, F_OK)) 
3215          self.assert_(access(point_general, F_OK)) 
3216          self.assert_(access(point_point, F_OK)) 
3217   
3218          # Open the file, and assert the chi2 value is as expected. 
3219          get_data = extract_data(file=map_name) 
3220   
3221          # Extract line 0, column 0. 
3222          test = float(get_data[line_chi2-1][0]) 
3223   
3224          # Assert. 
3225          self.assertAlmostEqual(test, pre_chi2,  6) 
3226   
3227   
3228 -    def test_dx_map_clustered_create_par_file(self): 
3229          """Test making dx_map for residues under clustered calculation, and the creation of the parameter file. 
3230   
3231          U{Task #7860<https://gna.org/task/index.php?7860>} : When dx_map is issued, create a parameter file which maps parameters to chi2 value. 
3232   
3233          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
3234          """ 
3235   
3236          # Define path to data  
3237          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+'surface_chi2_clustered_fitting' 
3238   
3239          # Read data. 
3240          self.interpreter.results.read(prev_data_path + sep + 'coMDD_-_TSMFK01_-_min_-_32_-_free_spins.bz2') 
3241   
3242          # Get residue of interest. 
3243          cur_spin_id = ":%i@%s"%(65, 'N') 
3244          cur_spin_id_str = cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_') 
3245   
3246          # Get the spin container. 
3247          cur_spin = return_spin(cur_spin_id) 
3248   
3249          # Get the chi2 value 
3250          pre_chi2 = cur_spin.chi2 
3251   
3252          # Then do a local minimisation. 
3253          #self.interpreter.select.spin(":%i@%s"%(2, 'N')) 
3254          self.interpreter.minimise.calculate() 
3255   
3256          # Get the chi2 value after calculation. 
3257          calc_chi2 = cur_spin.chi2 
3258   
3259          # Assert calculation is equal. 
3260          self.assertAlmostEqual(pre_chi2, calc_chi2) 
3261   
3262          # Define dx.map settings. 
3263          dx_inc = 2 
3264          dx_params = ['dw', 'k_AB', 'r2a'] 
3265          dx_point_clustered_min = [cur_spin.dw, cur_spin.k_AB, cur_spin.r2a['SQ CPMG - 499.86214000 MHz']] 
3266   
3267          print("Params for dx map is") 
3268          print(dx_params) 
3269          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3270          print(dx_point_clustered_min) 
3271   
3272          # Define file_names. 
3273          cur_model = 'TSMFK01' 
3274          file_name_map = "%s_map%s" % (cur_model, cur_spin_id_str) 
3275          file_name_point = "%s_point%s" % (cur_model, cur_spin_id_str) 
3276   
3277          # Determine bounds for lower and upper 
3278          lower = [dx_point_clustered_min[0], dx_point_clustered_min[1], dx_point_clustered_min[2]] 
3279          upper = [19.0, 2.4, 9.5] 
3280   
3281          # Define temporary folder. 
3282          result_dir = self.tmpdir 
3283   
3284          # For testing. 
3285          #result_dir = None 
3286          #self.interpreter.relax_disp.cluster(cluster_id='free spins', spin_id=cur_spin_id) 
3287   
3288          # Then do the map. 
3289          self.interpreter.dx.map(params=dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=dx_inc, lower=lower, upper=upper, axis_incs=10, file_prefix=file_name_map, dir=result_dir, point=dx_point_clustered_min, point_file=file_name_point, create_par_file=True) 
3290   
3291          # Print where to locate values. 
3292          nr_chi2_val = (dx_inc + 1)**3 
3293          print("Nr of chi2 calculations are=%i"%nr_chi2_val) 
3294          print("Global chi2=%3.3f, Calc_chi=%3.3f" % (pre_chi2, calc_chi2) ) 
3295   
3296          ## Check for file creation 
3297          # Set filepaths. 
3298          map_name = get_file_path(file_name=file_name_map, dir=result_dir) 
3299          map_cfg = get_file_path(file_name=file_name_map+".cfg", dir=result_dir) 
3300          map_net = get_file_path(file_name=file_name_map+".net", dir=result_dir) 
3301          map_general = get_file_path(file_name=file_name_map+".general", dir=result_dir) 
3302          map_par = get_file_path(file_name=file_name_map+".par", dir=result_dir) 
3303   
3304          point_general = get_file_path(file_name=file_name_point+".general", dir=result_dir) 
3305          point_point = get_file_path(file_name=file_name_point, dir=result_dir) 
3306   
3307          # Test the files exists. 
3308          self.assert_(access(map_cfg, F_OK)) 
3309          self.assert_(access(map_net, F_OK)) 
3310          self.assert_(access(map_general, F_OK)) 
3311          self.assert_(access(map_par, F_OK)) 
3312          self.assert_(access(point_general, F_OK)) 
3313          self.assert_(access(point_point, F_OK)) 
3314   
3315          print("\nParams for dx map is") 
3316          print(dx_params) 
3317          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3318          print(dx_point_clustered_min, "\n") 
3319   
3320          # Open the parameter chi2 file, and assert the chi2 value in the sorted parameter file is not lower that than the global minimisation. 
3321          get_data = extract_data(file=map_par) 
3322   
3323          # Extract line 1, column 9. 
3324          test = float(get_data[1][9]) 
3325   
3326          # Print data if map contain a lower value than the global minimised value. 
3327          if test < pre_chi2: 
3328              print("\nInitial clustered minimised chi2 value is=%3.3f, whereby the minimum map value is=%3.3f\n" % (pre_chi2, test)) 
3329              for line in get_data: 
3330                  print(line) 
3331   
3332          # Assert that the initial global chi2 is lower than the map value. 
3333   
3334          # The following test was taken out, since this a particular interesting case. 
3335          # There exist a double minimum, where relax has not found the global minimum. 
3336          # This is due to not grid searching for R2A, but using the minimum  
3337          #self.assert_(pre_chi2 < test) 
3338   
3339   
3340 -    def test_estimate_r2eff_err(self): 
3341          """Test the user function for estimating R2eff errors from exponential curve fitting. 
3342   
3343          This follows Task 7822. 
3344          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3345   
3346          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3347          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3348          """ 
3349   
3350          # Cluster residues 
3351          cluster_ids = [ 
3352          ":13@N", 
3353          ":15@N", 
3354          ":16@N", 
3355          ":25@N", 
3356          ":26@N", 
3357          ":28@N", 
3358          ":39@N", 
3359          ":40@N", 
3360          ":41@N", 
3361          ":43@N", 
3362          ":44@N", 
3363          ":45@N", 
3364          ":49@N", 
3365          ":52@N", 
3366          ":53@N"] 
3367   
3368          # Load the data. 
3369          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
3370   
3371          # The dispersion models. 
3372          MODELS = [MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
3373   
3374          # The grid search size (the number of increments per dimension). 
3375          GRID_INC = None 
3376   
3377          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
3378          MC_NUM = 3 
3379   
3380          # Model selection technique. 
3381          MODSEL = 'AIC' 
3382   
3383          # Execute the auto-analysis (fast). 
3384          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
3385          OPT_FUNC_TOL = 1e-25 
3386          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
3387          OPT_MAX_ITERATIONS = 10000000 
3388          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
3389   
3390          result_dir_name = ds.tmpdir 
3391   
3392          # Make all spins free 
3393          for curspin in cluster_ids: 
3394              self.interpreter.relax_disp.cluster('free spins', curspin) 
3395              # Shut them down 
3396              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
3397   
3398          # Select only a subset of spins for global fitting 
3399          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
3400          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
3401   
3402          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
3403          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
3404   
3405          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
3406          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
3407   
3408          # Set the model. 
3409          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
3410   
3411          # Check if intensity errors have already been calculated. 
3412          check_intensity_errors() 
3413   
3414          # Do a grid search. 
3415          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=11, constraints=True, verbosity=1) 
3416   
3417          # Minimise. 
3418          self.interpreter.minimise.execute(min_algor='Newton', constraints=False, verbosity=1) 
3419   
3420          # Estimate R2eff errors. 
3421          self.interpreter.relax_disp.r2eff_err_estimate() 
3422   
3423          r1_fit = True 
3424   
3425          # Run the analysis. 
3426          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, r1_fit=r1_fit) 
3427   
3428          # Verify the data. 
3429          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='direct') 
3430   
3431   
3432 -    def test_estimate_r2eff_err_auto(self): 
3433          """Test the user function for estimating R2eff errors from exponential curve fitting, via the auto_analyses menu. 
3434   
3435          This follows Task 7822. 
3436          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3437   
3438          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3439          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3440          """ 
3441   
3442          # Cluster residues 
3443          cluster_ids = [ 
3444          ":13@N", 
3445          ":15@N", 
3446          ":16@N", 
3447          ":25@N", 
3448          ":26@N", 
3449          ":28@N", 
3450          ":39@N", 
3451          ":40@N", 
3452          ":41@N", 
3453          ":43@N", 
3454          ":44@N", 
3455          ":45@N", 
3456          ":49@N", 
3457          ":52@N", 
3458          ":53@N"] 
3459   
3460          # Load the data. 
3461          #self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
3462          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep 
3463   
3464          # Set pipe name, bundle and type. 
3465          pipe_name = 'base pipe' 
3466          pipe_bundle = 'relax_disp' 
3467          pipe_type = 'relax_disp' 
3468   
3469          # Create the data pipe. 
3470          self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 
3471   
3472          file = data_path + '1_setup_r1rho_GUI.py' 
3473          self.interpreter.script(file=file, dir=None) 
3474   
3475          # The dispersion models. 
3476          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
3477   
3478          # The grid search size (the number of increments per dimension). 
3479          GRID_INC = None 
3480   
3481          # The number of Monte Carlo simulations to be used for error analysis for exponential curve fitting of R2eff. 
3482          # When set to minus 1, estimation of the errors will be extracted from the covariance matrix. 
3483          # This is HIGHLY likely to be wrong, but can be used in an initial test fase. 
3484          EXP_MC_NUM = -1 
3485   
3486          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
3487          MC_NUM = 3 
3488   
3489          # Model selection technique. 
3490          MODSEL = 'AIC' 
3491   
3492          # Execute the auto-analysis (fast). 
3493          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
3494          OPT_FUNC_TOL = 1e-25 
3495          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
3496          OPT_MAX_ITERATIONS = 10000000 
3497          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
3498   
3499          # Make all spins free 
3500          #for curspin in cluster_ids: 
3501          #    self.interpreter.relax_disp.cluster('free spins', curspin) 
3502          #    # Shut them down 
3503          #    self.interpreter.deselect.spin(spin_id=curspin, boolean='OR', change_all=False) 
3504   
3505          # Make all spins free 
3506          self.interpreter.deselect.spin(spin_id=':1-100', change_all=False) 
3507   
3508          # Select only a subset of spins for global fitting 
3509          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
3510          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
3511   
3512          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
3513          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
3514   
3515          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
3516          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
3517   
3518          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3519              print(spin_id) 
3520   
3521          result_dir_name = self.tmpdir 
3522          r1_fit = True 
3523   
3524          # Run the analysis. 
3525          relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, exp_mc_sim_num=EXP_MC_NUM, modsel=MODSEL, r1_fit=r1_fit) 
3526   
3527          # Verify the data. 
3528          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='direct') 
3529   
3530   
3531 -    def test_estimate_r2eff_err_methods(self): 
3532          """Test the user function for estimating R2eff and associated errors for exponential curve fitting with different methods. 
3533          This is compared with a run where erros are estimated by 2000 Monte Carlo simulations. 
3534   
3535          This follows Task 7822. 
3536          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3537   
3538          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3539          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3540   
3541          NOTE: The difference in the methods was due to a bug in relax! 
3542          U{bug #22554<https://gna.org/bugs/index.php?22554>}. The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected. 
3543   
3544          This dataset is old, and includes 2000 Monte-Carlo simulations, which is performed wrong. 
3545          """ 
3546   
3547          # Define data path. 
3548          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff" 
3549   
3550          # Create pipe. 
3551          self.interpreter.pipe.create('MC_2000', 'relax_disp') 
3552   
3553          # Read results for 2000 MC simulations. 
3554          self.interpreter.results.read(prev_data_path + sep + 'results') 
3555   
3556          # Start dic. 
3557          my_dic = {} 
3558          param_key_list = [] 
3559   
3560          # Do boot strapping ? 
3561          do_boot = True 
3562          if do_boot: 
3563              min_algor = 'Newton' 
3564              min_options = () 
3565              sim_boot = 200 
3566              scaling_list = [1.0, 1.0] 
3567   
3568          # First check sim values. 
3569          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3570              # Add key to dic. 
3571              my_dic[spin_id] = {} 
3572   
3573              # Loop over sim. 
3574              for i, r2eff_sim in enumerate(cur_spin.r2eff_sim): 
3575                  # Loop over all exp type. 
3576                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3577                      # Generate the param_key. 
3578                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3579                      r2eff_sim_point = r2eff_sim[param_key] 
3580                      i0_sim_point = cur_spin.r2eff_sim[i][param_key] 
3581   
3582                      # Assert point are higher than 0.0. 
3583                      #point_info = "r2eff=%3.2f i0=%3.2f, at %3.1f MHz, for offset=%3.3f ppm and dispersion point %-5.1f, at sim index %i." % (r2eff_sim_point, i0_sim_point, frq/1E6, offset, point, i) 
3584                      #print(point_info) 
3585                      self.assert_(r2eff_sim_point > 0.0) 
3586                      self.assert_(i0_sim_point > 0.0) 
3587   
3588          # Get the data. 
3589          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3590              # Generate spin string. 
3591              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
3592   
3593              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3594                  # Generate the param_key. 
3595                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3596   
3597                  # Loop over all sim, and collect data. 
3598                  r2eff_sim_l = [] 
3599                  i0_sim_l = [] 
3600                  for i, r2eff_sim in enumerate(cur_spin.r2eff_sim): 
3601                      i0_sim = cur_spin.i0_sim[i] 
3602   
3603                      r2eff_sim_i = r2eff_sim[param_key] 
3604                      r2eff_sim_l.append(r2eff_sim_i) 
3605                      i0_sim_i = i0_sim[param_key] 
3606                      i0_sim_l.append(i0_sim_i) 
3607   
3608                  # Take the standard deviation of all values. 
3609                  r2eff_sim_err = std(asarray(r2eff_sim_l), ddof=1) 
3610                  i0_sim_err = std(asarray(i0_sim_l), ddof=1) 
3611   
3612                  # Append key. 
3613                  param_key_list.append(param_key) 
3614   
3615                  # Add key to dic. 
3616                  my_dic[spin_id][param_key] = {} 
3617   
3618                  # Get the value. 
3619                  r2eff = getattr(cur_spin, 'r2eff')[param_key] 
3620                  r2eff_err = getattr(cur_spin, 'r2eff_err')[param_key] 
3621                  i0 = getattr(cur_spin, 'i0')[param_key] 
3622                  i0_err = getattr(cur_spin, 'i0_err')[param_key] 
3623   
3624                  # Save to dic. 
3625                  my_dic[spin_id][param_key]['r2eff'] = r2eff 
3626                  my_dic[spin_id][param_key]['r2eff_err'] = r2eff_err 
3627                  my_dic[spin_id][param_key]['i0'] = i0 
3628                  my_dic[spin_id][param_key]['i0_err'] = i0_err 
3629                  my_dic[spin_id][param_key]['r2eff_err_sim'] = r2eff_sim_err 
3630                  my_dic[spin_id][param_key]['i0_err_sim'] = i0_sim_err 
3631   
3632                  # Assert values are equal 
3633                  self.assertAlmostEqual(r2eff_sim_err, r2eff_err) 
3634                  self.assertAlmostEqual(i0_sim_err, i0_err) 
3635   
3636                  if do_boot: 
3637                      values = [] 
3638                      errors = [] 
3639                      times = [] 
3640                      for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
3641                          values.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)) 
3642                          errors.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)) 
3643                          times.append(time) 
3644   
3645                      # Convert to numpy array. 
3646                      values = asarray(values) 
3647                      errors = asarray(errors) 
3648                      times = asarray(times) 
3649   
3650                      R_m_sim_l = [] 
3651                      I0_m_sim_l = [] 
3652                      for j in range(sim_boot): 
3653                          if j in range(0, 100000, 100): 
3654                              print("Simulation %i"%j) 
3655                          # Start minimisation. 
3656   
3657                          # Produce errors 
3658                          I_err = [] 
3659                          for j, error in enumerate(errors): 
3660                              I_error = gauss(values[j], error) 
3661                              I_err.append(I_error) 
3662                          # Convert to numpy array. 
3663                          I_err = asarray(I_err) 
3664   
3665                          x0 = [r2eff, i0] 
3666                          model = Relax_fit_opt(model='exp', num_params=len(x0), values=I_err, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
3667   
3668                          params_minfx_sim_j, chi2_minfx_sim_j, iter_count, f_count, g_count, h_count, warning = generic_minimise(func=model.func, dfunc=model.dfunc, d2func=model.d2func, args=(), x0=x0, min_algor=min_algor, min_options=min_options, full_output=True, print_flag=0) 
3669                          R_m_sim_j, I0_m_sim_j = params_minfx_sim_j 
3670                          R_m_sim_l.append(R_m_sim_j) 
3671                          I0_m_sim_l.append(I0_m_sim_j) 
3672   
3673                      # Get stats on distribution. 
3674                      sigma_R_sim = std(asarray(R_m_sim_l), ddof=1) 
3675                      sigma_I0_sim = std(asarray(I0_m_sim_l), ddof=1) 
3676                      my_dic[spin_id][param_key]['r2eff_err_boot'] = sigma_R_sim 
3677                      my_dic[spin_id][param_key]['i0_err_boot'] = sigma_I0_sim 
3678   
3679   
3680          # A new data pipe. 
3681          self.interpreter.pipe.copy(pipe_from='MC_2000', pipe_to='r2eff_est') 
3682          self.interpreter.pipe.switch(pipe_name='r2eff_est') 
3683   
3684          # Delete old errors. 
3685          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3686              delattr(cur_spin, 'r2eff_err') 
3687              delattr(cur_spin, 'i0_err') 
3688   
3689          # Set the model. 
3690          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
3691   
3692          # Estimate R2eff and errors. 
3693          self.interpreter.relax_disp.r2eff_err_estimate(verbosity=0) 
3694   
3695          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3696              # Generate spin string. 
3697              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
3698   
3699              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3700                  # Generate the param_key. 
3701                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3702   
3703                  # Get the value. 
3704                  r2eff_est = getattr(cur_spin, 'r2eff')[param_key] 
3705                  r2eff_err_est = getattr(cur_spin, 'r2eff_err')[param_key] 
3706                  i0_est = getattr(cur_spin, 'i0')[param_key] 
3707                  i0_err_est = getattr(cur_spin, 'i0_err')[param_key] 
3708   
3709                  # Get from dic. 
3710                  r2eff = my_dic[spin_id][param_key]['r2eff'] 
3711                  r2eff_err = my_dic[spin_id][param_key]['r2eff_err'] 
3712                  i0 = my_dic[spin_id][param_key]['i0'] 
3713                  i0_err = my_dic[spin_id][param_key]['i0_err'] 
3714                  r2eff_sim_err = my_dic[spin_id][param_key]['r2eff_err_sim'] 
3715                  i0_sim_err = my_dic[spin_id][param_key]['i0_err_sim'] 
3716   
3717                  if do_boot: 
3718                      r2eff_boot_err = my_dic[spin_id][param_key]['r2eff_err_boot'] 
3719                      i0_boot_err = my_dic[spin_id][param_key]['i0_err_boot'] 
3720                  else: 
3721                      r2eff_boot_err = 0.0 
3722                      i0_boot_err = 0.0 
3723   
3724                  print("%s at %3.1f MHz, for offset=%3.3f ppm and dispersion point %-5.1f." % (exp_type, frq/1E6, offset, point) ) 
3725                  print("r2eff=%3.3f/%3.3f r2eff_err=%3.4f/%3.4f/%3.4f/%3.4f" % (r2eff, r2eff_est, r2eff_err, r2eff_err_est, r2eff_sim_err, r2eff_boot_err) ), 
3726                  print("i0=%3.3f/%3.3f i0_err=%3.4f/%3.4f/%3.4f/%3.4f\n" % (i0, i0_est, i0_err, i0_err_est, i0_sim_err, i0_boot_err) ) 
3727   
3728   
3729          # Now do it manually. 
3730          estimate_r2eff(method='scipy.optimize.leastsq') 
3731   
3732          estimate_r2eff(method='minfx', min_algor='simplex', c_code=True, constraints=False, chi2_jacobian=False) 
3733          estimate_r2eff(method='minfx', min_algor='simplex', c_code=True, constraints=False, chi2_jacobian=True) 
3734   
3735          estimate_r2eff(method='minfx', min_algor='simplex', c_code=False, constraints=False, chi2_jacobian=False) 
3736          estimate_r2eff(method='minfx', min_algor='simplex', c_code=False, constraints=False, chi2_jacobian=True) 
3737   
3738          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=True, constraints=False, chi2_jacobian=False) 
3739          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=True, constraints=False, chi2_jacobian=True) 
3740   
3741          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian=False) 
3742          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian=True) 
3743   
3744          estimate_r2eff(method='minfx', min_algor='Newton', c_code=True, constraints=False, chi2_jacobian=False) 
3745          estimate_r2eff(method='minfx', min_algor='Newton', c_code=True, constraints=False, chi2_jacobian=True) 
3746   
3747   
3748   
3749 -    def test_exp_fit(self): 
3750          """Test the relaxation dispersion 'exp_fit' model curve fitting.""" 
3751   
3752          # Execute the script. 
3753          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'exp_fit.py') 
3754   
3755          # The original exponential curve parameters. 
3756          res_data = [ 
3757              [15., 10., 20000., 25000.], 
3758              [12., 11., 50000., 51000.], 
3759              [17., 9., 100000., 96000.] 
3760          ] 
3761   
3762          # List of parameters which do not belong to the model. 
3763          blacklist = ['cpmg_frqs', 'r2', 'rex', 'kex', 'r2a', 'k_AB', 'dw'] 
3764   
3765          # Checks for each residue. 
3766          for i in range(len(res_data)): 
3767              # Printout. 
3768              print("\nResidue number %s." % (i+1)) 
3769   
3770              # Check the fitted parameters. 
3771              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_1000.000'], res_data[i][0], places=2) 
3772              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_2000.000'], res_data[i][1], places=2) 
3773              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_1000.000']/10000, res_data[i][2]/10000, places=3) 
3774              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_2000.000']/10000, res_data[i][3]/10000, places=3) 
3775   
3776              # Check the simulation errors. 
3777              self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_1000.000'] < 5.0) 
3778              self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_2000.000'] < 5.0) 
3779              self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_1000.000']/10000 < 5.0) 
3780              self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_2000.000']/10000 < 5.0) 
3781   
3782              # Check that certain parameters are not present. 
3783              for param in blacklist: 
3784                  print("\tChecking for the absence of the '%s' parameter." % param) 
3785                  self.assert_(not hasattr(cdp.mol[0].res[i].spin[0], param)) 
3786   
3787          # Check the clustering information. 
3788          self.assert_(hasattr(cdp, 'clustering')) 
3789          keys = ['free spins', 'cluster'] 
3790          for key in keys: 
3791              self.assert_(key in cdp.clustering) 
3792          self.assert_('test' not in cdp.clustering) 
3793          self.assertEqual(cdp.clustering['free spins'], [':2@N']) 
3794          self.assertEqual(cdp.clustering['cluster'], [':1@N', ':3@N']) 
3795   
3796   
3797 -    def test_finite_value(self): 
3798          """Test return from C code, when parameters are wrong.  This can happen, if minfx takes a wrong step.""" 
3799   
3800          times = array([ 0.7,  1.,  0.8,  0.4,  0.9]) 
3801          I = array([ 476.76174875,  372.43328777,  454.20339981,  656.87936253,  419.16726341]) 
3802          errors = array([  9.48032653,  11.34093541,   9.35149017,  10.84867928,  12.17590736]) 
3803   
3804          scaling_list = [1.0, 1.0] 
3805          model = Relax_fit_opt(model='exp', num_params=2, values=I, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
3806   
3807          R = - 500. 
3808          I0 = 1000. 
3809          params = [R, I0] 
3810   
3811          chi2 = model.func(params) 
3812   
3813          print("The chi2 value returned from C-code for R=%3.2f and I0=%3.2f, then chi2=%3.2f"%(R, I0, chi2)) 
3814          self.assertNotEqual(chi2, inf) 
3815   
3816   
3817 -    def test_hansen_catia_input(self): 
3818          """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CATIA. 
3819   
3820          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3821          """ 
3822   
3823          # Load the R2eff results file. 
3824          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 
3825          self.interpreter.results.read(file_name) 
3826          self.interpreter.deselect.spin(':4') 
3827   
3828          # The spin isotopes. 
3829          self.interpreter.spin.isotope("15N") 
3830   
3831          # Generate the input files. 
3832          self.interpreter.relax_disp.catia_input(dir=ds.tmpdir, force=True) 
3833   
3834          # Check the r2eff set files. 
3835          print("\nChecking the R2eff input set files.") 
3836          files = ['data_set_500.inp', 'data_set_500.inp'] 
3837          for file in files: 
3838              self.assert_(access(ds.tmpdir+sep+file, F_OK)) 
3839          data_set_500 = [ 
3840              "ID=500\n", 
3841              "Sfrq = 500\n", 
3842              "Temperature = 0.0\n", 
3843              "Nucleus = N15\n", 
3844              "Couplednucleus = H1\n", 
3845              "Time_equil = 0.0\n", 
3846              "Pwx_cp = 0.0\n", 
3847              "Taub = 0.0\n", 
3848              "Time_T2 = 0.03\n", 
3849              "Xcar = 0.0\n", 
3850              "Seqfil = CW_CPMG\n", 
3851              "Minerror = (2.%;0.5/s)\n", 
3852              "Basis = (Iph_7)\n", 
3853              "Format = (0;1;2)\n", 
3854              "DataDirectory = /tmp/tmpNjOGNG/input_r2eff\n", 
3855              "Data = (\n", 
3856              " [70N;spin_70_N_500.cpmg];\n", 
3857              " [71N;spin_71_N_500.cpmg];\n", 
3858              ")\n", 
3859          ] 
3860          file = open(ds.tmpdir+sep+files[0]) 
3861          lines = file.readlines() 
3862          file.close() 
3863          for i in range(len(data_set_500)): 
3864              # Skip the data directory, as this is a random file name. 
3865              if i == 14: 
3866                  continue 
3867   
3868              self.assertEqual(data_set_500[i], lines[i]) 
3869   
3870          # Check the r2eff files. 
3871          print("\nChecking the R2eff input files.") 
3872          files = ['spin_70_N_500.cpmg', 'spin_70_N_800.cpmg', 'spin_71_N_500.cpmg', 'spin_71_N_800.cpmg'] 
3873          for file in files: 
3874              self.assert_(access(ds.tmpdir+sep+'input_r2eff'+sep+file, F_OK)) 
3875          spin_70_N_500 = [ 
3876              "#        nu_cpmg(Hz)              R2(1/s)              Esd(R2)\n", 
3877              "  66.666600000000003   16.045540885533605    0.310924686180635\n", 
3878              " 133.333300000000008   14.877924861181727    0.303217270671013\n", 
3879              " 200.000000000000000   14.357820247260586    0.299894424543361\n", 
3880              " 266.666600000000017   12.664494620416516    0.289532060485796\n", 
3881              " 333.333300000000008   12.363204802467891    0.287759631749322\n", 
3882              " 400.000000000000000   11.092532381134513    0.280514035409862\n", 
3883              " 466.666600000000017   10.566090057649893    0.277618625949722\n", 
3884              " 533.333300000000008    9.805806894657803    0.273544382200754\n", 
3885              " 600.000000000000000    9.564300692201730    0.272276309984954\n", 
3886              " 666.666600000000017    9.015633750407980    0.269441511838159\n", 
3887              " 733.333300000000008    8.607764958055581    0.267375134391053\n", 
3888              " 800.000000000000000    8.279997179221338    0.265739551961997\n", 
3889              " 866.666600000000017    8.474535940963516    0.266707642726566\n", 
3890              " 933.333300000000008    8.158972897365194    0.265141210539941\n", 
3891              "1000.000000000000000    7.988630509501972    0.264304105548559\n", 
3892          ] 
3893          file = open(ds.tmpdir+sep+'input_r2eff'+sep+files[0]) 
3894          lines = file.readlines() 
3895          file.close() 
3896          for i in range(len(lines)): 
3897              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
3898          for i in range(len(spin_70_N_500)): 
3899              self.assertEqual(spin_70_N_500[i], lines[i]) 
3900   
3901          # Check the main file. 
3902          print("\nChecking the main CATIA execution file.") 
3903          main_file = [ 
3904              "ReadDataset(data_set_500.inp)\n", 
3905              "ReadDataset(data_set_800.inp)\n", 
3906              "ReadParam_Global(ParamGlobal.inp)\n", 
3907              "ReadParam_Local(ParamSet1.inp)\n", 
3908              "\n", 
3909              "FreeLocalParam(all;Omega;false)\n", 
3910              "FreeLocalParam(all;R1iph_500;false)\n", 
3911              "FreeLocalParam(all;R1iph_800;false)\n", 
3912              "\n", 
3913              "Minimize(print=y;tol=1e-25;maxiter=10000000)\n", 
3914              "\n", 
3915              "PrintParam(output/GlobalParam.fit;global)\n", 
3916              "PrintParam(output/DeltaOmega.fit;DeltaO)\n", 
3917              "PrintData(output/)\n", 
3918              "\n", 
3919              "ChiSq(all;all)\n", 
3920              "exit(0)\n" 
3921          ] 
3922          file = open("%s%sFit.catia" % (ds.tmpdir, sep)) 
3923          lines = file.readlines() 
3924          file.close() 
3925          for i in range(len(main_file)): 
3926              self.assertEqual(main_file[i], lines[i]) 
3927   
3928   
3929 -    def test_hansen_cpmg_data_auto_analysis(self): 
3930          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 
3931   
3932          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3933          """ 
3934   
3935          # Set the model. 
3936          ds.models = [ 
3937              MODEL_NOREX, 
3938              MODEL_LM63, 
3939              MODEL_CR72, 
3940              MODEL_IT99 
3941          ] 
3942   
3943          # Execute the script. 
3944          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 
3945          self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 
3946   
3947          # The R20 keys. 
3948          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
3949          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
3950   
3951          # The 'No Rex' model checks. 
3952          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
3953          spin70 = return_spin(":70") 
3954          spin71 = return_spin(":71") 
3955          print("\n\nOptimised parameters:\n") 
3956          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3957          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3958          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3959          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3960          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
3961          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
3962          self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 
3963          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
3964          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
3965          self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 
3966   
3967          # The 'LM63' model checks. 
3968          self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 
3969          spin70 = return_spin(":70") 
3970          spin71 = return_spin(":71") 
3971          print("\n\nOptimised parameters:\n") 
3972          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3973          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3974          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3975          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
3976          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
3977          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3978          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 
3979          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 
3980          self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 
3981          self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 
3982          self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 
3983          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 
3984          self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 
3985          self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 
3986          self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 
3987          self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 
3988   
3989          # The 'CR72' model checks. 
3990          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
3991          spin70 = return_spin(":70") 
3992          spin71 = return_spin(":71") 
3993          print("\n\nOptimised parameters:\n") 
3994          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3995          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3996          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3997          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
3998          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
3999          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4000          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4001          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4002          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4003          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4004          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4005          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4006          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4007          self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 
4008          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 
4009          self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 
4010          self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 
4011          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 
4012          self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 
4013   
4014   
4015 -    def test_hansen_cpmg_data_auto_analysis_numeric(self): 
4016          """Test of the numeric model only dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 
4017   
4018          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4019          """ 
4020   
4021          # Set the model and numeric flag. 
4022          ds.models = [ 
4023              MODEL_NOREX, 
4024              MODEL_CR72, 
4025              MODEL_NS_CPMG_2SITE_EXPANDED 
4026          ] 
4027          ds.numeric_only = True 
4028   
4029          # Execute the script. 
4030          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 
4031   
4032          # The R20 keys. 
4033          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4034          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4035   
4036          # The 'No Rex' model checks. 
4037          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4038          spin70 = return_spin(":70") 
4039          spin71 = return_spin(":71") 
4040          print("\n\nOptimised parameters:\n") 
4041          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4042          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4043          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4044          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4045          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
4046          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
4047          self.assertAlmostEqual(spin70.chi2/10000, 8973.84810025761/10000, 3) 
4048          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
4049          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
4050          self.assertAlmostEqual(spin71.chi2/10000, 3908.00127830003/10000, 3) 
4051   
4052          # The 'CR72' model checks. 
4053          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4054          spin70 = return_spin(":70") 
4055          spin71 = return_spin(":71") 
4056          print("\n\nOptimised parameters:\n") 
4057          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4058          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4059          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4060          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4061          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4062          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4063          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4064          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4065          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4066          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4067          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4068          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4069          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4070          self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 
4071          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 
4072          self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 
4073          self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 
4074          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 
4075          self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 
4076   
4077          # The 'NS CPMG 2-site expanded' model checks. 
4078          self.interpreter.pipe.switch(pipe_name='NS CPMG 2-site expanded - relax_disp') 
4079          spin70 = return_spin(":70") 
4080          spin71 = return_spin(":71") 
4081          print("\n\nOptimised parameters:\n") 
4082          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4083          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4084          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4085          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4086          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4087          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4088          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4089          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95815351460902, 3) 
4090          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39649535771294, 3) 
4091          self.assertAlmostEqual(spin70.pA, 0.989701014493195, 3) 
4092          self.assertAlmostEqual(spin70.dw, 5.67314464776128, 3) 
4093          self.assertAlmostEqual(spin70.kex/10000, 1713.65380495429/10000, 3) 
4094          self.assertAlmostEqual(spin70.chi2, 52.5106880917473, 3) 
4095          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99889337382435, 3) 
4096          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89822887466673, 3) 
4097          self.assertAlmostEqual(spin71.pA, 0.986709050819695, 3) 
4098          self.assertAlmostEqual(spin71.dw, 2.09238266766502, 2) 
4099          self.assertAlmostEqual(spin71.kex/10000, 2438.27019901422/10000, 3) 
4100          self.assertAlmostEqual(spin71.chi2, 15.1644906963987, 3) 
4101   
4102          # The final data pipe checks. 
4103          self.interpreter.pipe.switch(pipe_name='final - relax_disp') 
4104          spin70 = return_spin(":70") 
4105          spin71 = return_spin(":71") 
4106          self.assertEqual(spin70.model, 'NS CPMG 2-site expanded') 
4107          self.assertEqual(spin71.model, 'NS CPMG 2-site expanded') 
4108   
4109   
4110 -    def test_hansen_cpmg_data_auto_analysis_r2eff(self): 
4111          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data (using the R2eff data directly instead of peak intensities). 
4112   
4113          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4114          """ 
4115   
4116          # Set the model. 
4117          ds.models = [ 
4118              MODEL_NOREX, 
4119              MODEL_LM63, 
4120              MODEL_CR72, 
4121              MODEL_IT99 
4122          ] 
4123   
4124          # Execute the script. 
4125          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_r2eff_data.py') 
4126          self.interpreter.state.save('analysis_r2eff', dir=ds.tmpdir, force=True) 
4127   
4128          # The R20 keys. 
4129          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4130          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4131   
4132          # The 'No Rex' model checks. 
4133          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4134          spin70 = return_spin(":70") 
4135          spin71 = return_spin(":71") 
4136          print("\n\nOptimised parameters:\n") 
4137          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4138          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4139          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4140          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4141          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
4142          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
4143          self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 
4144          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
4145          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
4146          self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 
4147   
4148          # The 'LM63' model checks. 
4149          self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 
4150          spin70 = return_spin(":70") 
4151          spin71 = return_spin(":71") 
4152          print("\n\nOptimised parameters:\n") 
4153          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4154          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4155          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4156          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4157          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4158          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4159          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 
4160          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 
4161          self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 
4162          self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 
4163          self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 
4164          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 
4165          self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 
4166          self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 
4167          self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 
4168          self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 
4169   
4170          # The 'CR72' model checks. 
4171          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4172          spin70 = return_spin(":70") 
4173          spin71 = return_spin(":71") 
4174          print("\n\nOptimised parameters:\n") 
4175          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4176          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4177          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4178          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4179          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4180          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4181          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4182          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4183          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4184          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4185          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4186          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4187          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4188          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00317154730225, 3) 
4189          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797713541, 3) 
4190          self.assertAlmostEqual(spin71.pA, 0.985922406429147, 3) 
4191          self.assertAlmostEqual(spin71.dw, 2.00500965887772, 2) 
4192          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579804/10000, 3) 
4193          self.assertAlmostEqual(spin71.chi2, 15.6595374288635, 3) 
4194   
4195   
4196 -    def test_hansen_cpmg_data_missing_auto_analysis(self): 
4197          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data with parts missing. 
4198   
4199          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4200          """ 
4201   
4202          # Set the model. 
4203          ds.models = [ 
4204              MODEL_R2EFF, 
4205              MODEL_NOREX, 
4206              MODEL_CR72, 
4207              MODEL_NS_CPMG_2SITE_EXPANDED 
4208          ] 
4209   
4210          # Execute the script. 
4211          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data_missing.py') 
4212          self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 
4213   
4214          # The R20 keys. 
4215          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4216          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4217   
4218          # The 'No Rex' model checks. 
4219          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4220          spin4 = return_spin(":4") 
4221          spin70 = return_spin(":70") 
4222          spin71 = return_spin(":71") 
4223          print("\n\nOptimised parameters:\n") 
4224          print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 
4225          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4226          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4227          print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 
4228          self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463084515171, 3) 
4229          self.assertAlmostEqual(spin4.r2[r20_key2], 1.63220784651911, 3) 
4230          self.assertAlmostEqual(spin4.chi2, 26.7356700694891, 3) 
4231          self.assertAlmostEqual(spin70.r2[r20_key1], 10.534285641325, 3) 
4232          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112794857068, 3) 
4233          self.assertAlmostEqual(spin70.chi2, 8973.84809774722, 3) 
4234          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83136858890037, 3) 
4235          self.assertAlmostEqual(spin71.chi2, 182.60081909193, 3) 
4236   
4237          # The 'CR72' model checks. 
4238          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4239          spin4 = return_spin(":4") 
4240          spin70 = return_spin(":70") 
4241          spin71 = return_spin(":71") 
4242          print("\n\nOptimised parameters:\n") 
4243          print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 
4244          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4245          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4246          print("%-20s %20.15g %20.15g %20.15g" % ("pA", spin4.pA, spin70.pA, spin71.pA)) 
4247          print("%-20s %20.15g %20.15g %20.15g" % ("dw", spin4.dw, spin70.dw, spin71.dw)) 
4248          print("%-20s %20.15g %20.15g %20.15g" % ("kex", spin4.kex, spin70.kex, spin71.kex)) 
4249          print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 
4250          self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463650370664, 2) 
4251          self.assertAlmostEqual(spin4.r2[r20_key2], 1.63221675941434, 3) 
4252          #self.assertAlmostEqual(spin4.pA, 0.818979078699935, 3)    # As dw (and kex) is zero, this parameter is not stable. 
4253          self.assertAlmostEqual(spin4.dw, 0.0, 2) 
4254          self.assertAlmostEqual(spin4.kex/10000, 0.0, 3) 
4255          self.assertAlmostEqual(spin4.chi2/100, 26.7356711142038/100, 3) 
4256          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97268077496405, 3) 
4257          self.assertAlmostEqual(spin70.r2[r20_key2], 9.41028133407727, 3) 
4258          self.assertAlmostEqual(spin70.pA, 0.989856641885939, 3) 
4259          self.assertAlmostEqual(spin70.dw, 5.60889911049405, 3) 
4260          self.assertAlmostEqual(spin70.kex/10000, 1752.62025618632/10000, 3) 
4261          self.assertAlmostEqual(spin70.chi2, 53.8382196964083, 3) 
4262          self.assertAlmostEqual(spin71.r2[r20_key1], 4.98123328466942, 3) 
4263          self.assertAlmostEqual(spin71.pA, 0.996607425484157, 3) 
4264          self.assertAlmostEqual(spin71.dw, 4.34346257383825, 2) 
4265          self.assertAlmostEqual(spin71.kex/10000, 1936.73197158804/10000, 3) 
4266          self.assertAlmostEqual(spin71.chi2, 5.51703791653689, 3) 
4267   
4268   
4269 -    def test_hansen_cpmg_data_to_cr72(self): 
4270          """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 dispersion model. 
4271   
4272          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4273          """ 
4274   
4275          # Base data setup. 
4276          self.setup_hansen_cpmg_data(model='CR72') 
4277   
4278          # Alias the spins. 
4279          spin70 = return_spin(":70") 
4280          spin71 = return_spin(":71") 
4281   
4282          # The R20 keys. 
4283          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4284          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4285   
4286          # Set the initial parameter values. 
4287          spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 
4288          spin70.pA = 0.9 
4289          spin70.dw = 6.0 
4290          spin70.kex = 1500.0 
4291          spin71.r2 = {r20_key1: 5, r20_key2: 9.0} 
4292          spin71.pA = 0.9 
4293          spin71.dw = 4.0 
4294          spin71.kex = 1900.0 
4295   
4296          # Low precision optimisation. 
4297          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4298   
4299          # Printout. 
4300          print("\n\nOptimised parameters:\n") 
4301          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4302          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4303          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4304          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4305          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4306          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4307          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4308   
4309          # Checks for residue :70. 
4310          self.assertAlmostEqual(spin70.r2[r20_key1], 6.9724581325007, 4) 
4311          self.assertAlmostEqual(spin70.r2[r20_key2], 9.40968331038162, 2) 
4312          self.assertAlmostEqual(spin70.pA, 0.989856656702431, 4) 
4313          self.assertAlmostEqual(spin70.dw, 5.60885879594746, 3) 
4314          self.assertAlmostEqual(spin70.kex/1000, 1752.91052702273/1000, 3) 
4315          self.assertAlmostEqual(spin70.chi2, 53.8382133597495, 4) 
4316   
4317          # Checks for residue :71. 
4318          self.assertAlmostEqual(spin71.r2[r20_key1], 5.0030740940524, 4) 
4319          self.assertAlmostEqual(spin71.pA, 0.985941082507823, 4) 
4320          self.assertAlmostEqual(spin71.dw, 2.00640384113696, 4) 
4321          self.assertAlmostEqual(spin71.kex/1000, 2480.79614442041/1000, 4) 
4322          self.assertAlmostEqual(spin71.chi2, 15.6595388312451, 4) 
4323   
4324          # Test the conversion to k_AB from kex and pA. 
4325          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4326          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4327   
4328          # Test the conversion to k_BA from kex and pA. 
4329          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4330          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4331   
4332   
4333 -    def test_hansen_cpmg_data_to_cr72_full(self): 
4334          """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 full dispersion model. 
4335   
4336          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4337          """ 
4338   
4339          # Base data setup. 
4340          self.setup_hansen_cpmg_data(model='CR72 full') 
4341   
4342          # Alias the spins. 
4343          spin70 = return_spin(":70") 
4344          spin71 = return_spin(":71") 
4345   
4346          # The R20 keys. 
4347          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4348          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4349   
4350          # Set the initial parameter values. 
4351          spin70.r2a = {r20_key1: 7.0, r20_key2: 9.0} 
4352          spin70.r2b = {r20_key1: 7.0, r20_key2: 9.0} 
4353          spin70.pA = 0.9 
4354          spin70.dw = 6.0 
4355          spin70.kex = 1500.0 
4356          spin71.r2a = {r20_key1: 5.0, r20_key2: 9.0} 
4357          spin71.r2b = {r20_key1: 5.0, r20_key2: 9.0} 
4358          spin71.pA = 0.9 
4359          spin71.dw = 4.0 
4360          spin71.kex = 1900.0 
4361   
4362          # Low precision optimisation. 
4363          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4364   
4365          # Printout. 
4366          print("\n\nOptimised parameters:\n") 
4367          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4368          print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 
4369          print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 
4370          print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 
4371          print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 
4372          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4373          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4374          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4375          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4376   
4377          # Checks for residue :70. 
4378          self.assertAlmostEqual(spin70.r2a[r20_key1], 6.87485258365614, 4) 
4379          self.assertAlmostEqual(spin70.r2b[r20_key1], 1.26075839074614, 4) 
4380          self.assertAlmostEqual(spin70.r2a[r20_key2], 8.79580446260797, 4) 
4381          self.assertAlmostEqual(spin70.r2b[r20_key2], 51.188411562843, 4) 
4382          self.assertAlmostEqual(spin70.pA, 0.989384178573802, 4) 
4383          self.assertAlmostEqual(spin70.dw, 5.54738203723682, 4) 
4384          self.assertAlmostEqual(spin70.kex/1000, 1831.4566463179/1000, 4) 
4385          self.assertAlmostEqual(spin70.chi2, 50.450410782403, 4) 
4386   
4387          # Checks for residue :71. 
4388          self.assertAlmostEqual(spin71.r2a[r20_key1], 5.04185695754972, 4) 
4389          self.assertAlmostEqual(spin71.r2b[r20_key1], 1.62857899941921, 4) 
4390          self.assertAlmostEqual(spin71.pA, 0.988832866751676, 4) 
4391          self.assertAlmostEqual(spin71.dw, 2.24905251856265, 4) 
4392          self.assertAlmostEqual(spin71.kex/1000, 2397.64122642946/1000, 4) 
4393          self.assertAlmostEqual(spin71.chi2, 15.8586492923672, 4) 
4394   
4395          # Test the conversion to k_AB from kex and pA. 
4396          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4397          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4398   
4399          # Test the conversion to k_BA from kex and pA. 
4400          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4401          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4402   
4403   
4404 -    def test_hansen_cpmg_data_to_it99(self): 
4405          """Optimisation of Dr. Flemming Hansen's CPMG data to the IT99 dispersion model. 
4406   
4407          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4408          """ 
4409   
4410          # Base data setup. 
4411          self.setup_hansen_cpmg_data(model='IT99') 
4412   
4413          # Alias the spins. 
4414          spin70 = return_spin(":70") 
4415          spin71 = return_spin(":71") 
4416   
4417          # The R20 keys. 
4418          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4419          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4420   
4421          # Set the initial parameter values. 
4422          spin70.r2 = {r20_key1: 8.8, r20_key2: 16.6} 
4423          spin70.dw = 10.0 
4424          spin70.pA = 0.5 
4425          spin70.tex = 1000.09 
4426          spin71.r2 = {r20_key1: 1.0, r20_key2: 1.0} 
4427          spin71.dw = 10.0 
4428          spin71.pA = 0.95 
4429          spin71.tex = 0.1 
4430   
4431          # Low precision optimisation. 
4432          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-10, grad_tol=None, max_iter=10000, constraints=True, scaling=True, verbosity=1) 
4433   
4434          # Printout. 
4435          print("\n\nOptimised parameters:\n") 
4436          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4437          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4438          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4439          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4440          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4441          print("%-20s %20.15g %20.15g" % ("tex", spin70.tex, spin71.tex)) 
4442          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4443   
4444          # Checks for residue :70. 
4445          self.assertAlmostEqual(spin70.r2[r20_key1], 7.24471197811838, 4) 
4446          self.assertAlmostEqual(spin70.r2[r20_key2], 10.0571040704729, 4) 
4447          self.assertAlmostEqual(spin70.dw, 5.2116923222744, 4) 
4448          self.assertAlmostEqual(spin70.pA, 0.990253627907212, 4) 
4449          self.assertAlmostEqual(spin70.tex*1000, 0.000638394793480444*1000, 4) 
4450          self.assertAlmostEqual(spin70.chi2, 93.5135798618747, 4) 
4451   
4452          # Checks for residue :71. 
4453          self.assertAlmostEqual(spin71.r2[r20_key1], 5.05971235970214, 4) 
4454          self.assertAlmostEqual(spin71.r2[r20_key2], 6.96641194493447, 4) 
4455          self.assertAlmostEqual(spin71.dw, 0.435389946897141, 4) 
4456          self.assertAlmostEqual(spin71.pA, 0.500000000213519, 3) 
4457          self.assertAlmostEqual(spin71.tex*1000, 0.000372436400585538*1000, 4) 
4458          self.assertAlmostEqual(spin71.chi2, 23.7895798801404, 4) 
4459   
4460   
4461 -    def test_hansen_cpmg_data_to_lm63(self): 
4462          """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 
4463   
4464          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4465          """ 
4466   
4467          # Base data setup. 
4468          self.setup_hansen_cpmg_data(model='LM63') 
4469   
4470          # Alias the spins. 
4471          spin70 = return_spin(":70") 
4472          spin71 = return_spin(":71") 
4473   
4474          # The R20 keys. 
4475          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4476          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4477   
4478          # Set the initial parameter values. 
4479          spin70.r2 = {r20_key1: 7.0, r20_key2: 7.0} 
4480          spin70.phi_ex = 0.3 
4481          spin70.kex = 5000.0 
4482          spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 
4483          spin71.phi_ex = 0.1 
4484          spin71.kex = 2500.0 
4485   
4486          # Low precision optimisation. 
4487          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 
4488   
4489          # Printout. 
4490          print("\n\nOptimised parameters:\n") 
4491          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4492          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4493          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4494          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4495          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4496          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4497   
4498          # Checks for residue :70. 
4499          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74362294539099) 
4500          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406797067481, 6) 
4501          self.assertAlmostEqual(spin70.phi_ex, 0.312733013751449) 
4502          self.assertAlmostEqual(spin70.kex/1000, 4723.09897146338/1000, 6) 
4503          self.assertAlmostEqual(spin70.chi2, 363.534044873483) 
4504   
4505          # Checks for residue :71. 
4506          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00776657729728, 5) 
4507          self.assertAlmostEqual(spin71.phi_ex, 0.0553787825650613, 5) 
4508          self.assertAlmostEqual(spin71.kex/1000, 2781.72292994154/1000, 5) 
4509          self.assertAlmostEqual(spin71.chi2, 17.0776399916287, 5) 
4510   
4511   
4512 -    def test_hansen_cpmg_data_to_lm63_3site(self): 
4513          """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 
4514   
4515          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4516          """ 
4517   
4518          # Base data setup. 
4519          self.setup_hansen_cpmg_data(model='LM63 3-site') 
4520   
4521          # Alias the spins. 
4522          spin70 = return_spin(":70") 
4523          spin71 = return_spin(":71") 
4524   
4525          # The R20 keys. 
4526          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4527          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4528   
4529          ## Set the initial parameter values. 
4530          spin70.r2 = {r20_key1: 7.570370921220954, r20_key2: 8.694446951909107} 
4531          spin70.phi_ex_B = 0.14872003058250227 
4532          spin70.phi_ex_C = 0.1319419923472704 
4533          spin70.kB = 4103.672910444741 
4534          spin70.kC = 7029.001690726248 
4535          spin71.r2 = {r20_key1: 5.1347793381636, r20_key2: 7.156573986051575} 
4536          spin71.phi_ex_B = 0.04013553485505605 
4537          spin71.phi_ex_C = 0.020050748406928887 
4538          spin71.kB = 4045.3007136121364 
4539          spin71.kC = 3586.38798270774 
4540   
4541          #self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
4542          #self.interpreter.minimise.grid_search(lower=None, upper=None, inc=41, constraints=True, verbosity=1) 
4543   
4544          # Low precision optimisation. 
4545          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 
4546   
4547          # Printout. 
4548          print("\n\nOptimised parameters:\n") 
4549          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4550          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4551          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4552          print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin70.phi_ex_B, spin71.phi_ex_B)) 
4553          print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin70.phi_ex_C, spin71.phi_ex_C)) 
4554          print("%-20s %20.15g %20.15g" % ("kB", spin70.kB, spin71.kB)) 
4555          print("%-20s %20.15g %20.15g" % ("kC", spin70.kC, spin71.kC)) 
4556          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4557   
4558          # Checks for residue :70. 
4559          self.assertAlmostEqual(spin70.r2[r20_key1], 6.7436230253685, 5) 
4560          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406813008828, 6) 
4561          self.assertAlmostEqual(spin70.phi_ex_B, 0.206304023079778, 5) 
4562          self.assertAlmostEqual(spin70.phi_ex_C, 0.106428983339627, 5) 
4563          self.assertAlmostEqual(spin70.kB/1000, 4723.09897652589/1000, 6) 
4564          self.assertAlmostEqual(spin70.kC/1000, 4723.09876196409/1000, 6) 
4565          self.assertAlmostEqual(spin70.chi2, 363.534044873483, 5) 
4566   
4567          # Checks for residue :71. 
4568          self.assertAlmostEqual(spin71.r2[r20_key1], 4.96612095596752, 5) 
4569          self.assertAlmostEqual(spin71.phi_ex_B, 0.00398262266512895, 5) 
4570          self.assertAlmostEqual(spin71.phi_ex_C, 0.0555791581291262, 5) 
4571          self.assertAlmostEqual(spin71.kB/1000, 1323.33195689832/1000, 5) 
4572          self.assertAlmostEqual(spin71.kC/1000, 3149.58971568059/1000, 5) 
4573          self.assertAlmostEqual(spin71.chi2, 16.2620934464368) 
4574   
4575   
4576 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_3D(self): 
4577          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D' dispersion model. 
4578   
4579          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4580          """ 
4581   
4582          # Base data setup. 
4583          self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D') 
4584   
4585          # Alias the spins. 
4586          spin70 = return_spin(":70") 
4587          spin71 = return_spin(":71") 
4588   
4589          # The R20 keys. 
4590          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4591          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4592   
4593          # Set the initial parameter values. 
4594          spin70.r2 = {r20_key1: 6.994165925, r20_key2: 9.428129427} 
4595          spin70.pA = 0.9897754407 
4596          spin70.dw = 5.642418428 
4597          spin70.kex = 1743.666375 
4598          spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 
4599          spin71.pA = 0.9968032899 
4600          spin71.dw = 4.577891393 
4601          spin71.kex = 1830.044597 
4602   
4603          # Low precision optimisation. 
4604          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4605   
4606          # Printout. 
4607          print("\n\nOptimised parameters:\n") 
4608          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4609          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4610          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4611          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4612          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4613          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4614          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4615   
4616          # Checks for residue :70. 
4617          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95797760459016, 4) 
4618          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39628959312699, 4) 
4619          self.assertAlmostEqual(spin70.pA, 0.989700985380975, 4) 
4620          self.assertAlmostEqual(spin70.dw, 5.6733714171086, 4) 
4621          self.assertAlmostEqual(spin70.kex/1000, 1713.63101361545/1000, 4) 
4622          self.assertAlmostEqual(spin70.chi2, 52.5106928523775, 4) 
4623   
4624          # Checks for residue :71. 
4625          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99893565849977, 4) 
4626          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89825625944034, 4) 
4627          self.assertAlmostEqual(spin71.pA, 0.986716058519642, 4) 
4628          self.assertAlmostEqual(spin71.dw, 2.09292495350993, 4) 
4629          self.assertAlmostEqual(spin71.kex/1000, 2438.04423541463/1000, 4) 
4630          self.assertAlmostEqual(spin71.chi2, 15.164490242352, 4) 
4631   
4632          # Test the conversion to k_AB from kex and pA. 
4633          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4634          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4635   
4636          # Test the conversion to k_BA from kex and pA. 
4637          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4638          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4639   
4640   
4641 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_3D_full(self): 
4642          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D full' dispersion model. 
4643   
4644          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4645          """ 
4646   
4647          # Base data setup. 
4648          self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D full') 
4649   
4650          # Alias the spins. 
4651          spin70 = return_spin(":70") 
4652          spin71 = return_spin(":71") 
4653   
4654          # The R20 keys. 
4655          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4656          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4657   
4658          # Set the initial parameter values. 
4659          spin70.r2a = {r20_key1: 6.644753428, r20_key2: 7.891776687} 
4660          spin70.r2b = {r20_key1: 7.163478485, r20_key2: 138.5170395} 
4661          spin70.pA = 0.9884781357 
4662          spin70.dw = 5.456507396 
4663          spin70.kex = 1906.521189 
4664          spin71.r2a = {r20_key1: 4.99893524108981, r20_key2: 100.0} 
4665          spin71.r2b = {r20_key1: 8.27456243639973, r20_key2: 100.0} 
4666          spin71.pA = 0.986709616684097 
4667          spin71.dw = 2.09245158280905 
4668          spin71.kex = 2438.2766211401 
4669   
4670          # Low precision optimisation. 
4671          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4672   
4673          # Printout. 
4674          print("\n\nOptimised parameters:\n") 
4675          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4676          print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 
4677          print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 
4678          print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 
4679          print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 
4680          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4681          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4682          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4683          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4684   
4685          # Checks for residue :70. 
4686          self.assertAlmostEqual(spin70.r2a[r20_key1], 6.61176004043484, 4) 
4687          self.assertAlmostEqual(spin70.r2b[r20_key1], 7.4869316381241, 4) 
4688          self.assertAlmostEqual(spin70.r2a[r20_key2], 7.78200386067591, 4) 
4689          self.assertAlmostEqual(spin70.r2b[r20_key2], 141.703593742468, 4) 
4690          self.assertAlmostEqual(spin70.pA, 0.988404987055969, 4) 
4691          self.assertAlmostEqual(spin70.dw, 5.4497360203213, 4) 
4692          self.assertAlmostEqual(spin70.kex/1000, 1934.09304607082/1000, 4) 
4693          self.assertAlmostEqual(spin70.chi2, 44.6793752187925, 4) 
4694   
4695          # Checks for residue :71. 
4696          self.assertAlmostEqual(spin71.r2a[r20_key1], 4.6013095731966, 4) 
4697          self.assertAlmostEqual(spin71.r2b[r20_key1], 13.3245678276332, 4) 
4698          self.assertAlmostEqual(spin71.r2a[r20_key2], 2.08243621257779, 4) 
4699          self.assertAlmostEqual(spin71.r2b[r20_key2], 153.355765094575, 4) 
4700          self.assertAlmostEqual(spin71.pA, 0.9665748685124, 4) 
4701          self.assertAlmostEqual(spin71.dw, 1.41898001408953, 4) 
4702          self.assertAlmostEqual(spin71.kex/1000, 2580.65795560688/1000, 4) 
4703          self.assertAlmostEqual(spin71.chi2, 13.4937006732165, 4) 
4704   
4705          # Test the conversion to k_AB from kex and pA. 
4706          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4707          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4708   
4709          # Test the conversion to k_BA from kex and pA. 
4710          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4711          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4712   
4713   
4714 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_expanded(self): 
4715          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site expanded' dispersion model. 
4716   
4717          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4718          """ 
4719   
4720          # Base data setup. 
4721          self.setup_hansen_cpmg_data(model='NS CPMG 2-site expanded') 
4722   
4723          # Alias the spins. 
4724          spin70 = return_spin(":70") 
4725          spin71 = return_spin(":71") 
4726   
4727          # The R20 keys. 
4728          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4729          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4730   
4731          # Set the initial parameter values. 
4732          spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 
4733          spin70.pA = 0.9 
4734          spin70.dw = 6.0 
4735          spin70.kex = 1500.0 
4736          spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 
4737          spin71.pA = 0.9 
4738          spin71.dw = 4.0 
4739          spin71.kex = 1900.0 
4740   
4741          # Low precision optimisation. 
4742          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4743   
4744          # Printout. 
4745          print("\n\nOptimised parameters:\n") 
4746          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4747          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4748          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4749          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4750          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4751          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4752          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4753   
4754          # Checks for residue :70. 
4755          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95813330991529, 4) 
4756          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39663480561524, 4) 
4757          self.assertAlmostEqual(spin70.pA, 0.989700843879574, 4) 
4758          self.assertAlmostEqual(spin70.dw, 5.67315878825691, 4) 
4759          self.assertAlmostEqual(spin70.kex/1000, 1713.56110716632/1000, 4) 
4760          self.assertAlmostEqual(spin70.chi2, 52.5106879242812, 4) 
4761   
4762          # Checks for residue :71. 
4763          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99881666793312, 4) 
4764          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89817482453042, 4) 
4765          self.assertAlmostEqual(spin71.pA, 0.986712911453639, 4) 
4766          self.assertAlmostEqual(spin71.dw, 2.09273069372236, 4) 
4767          self.assertAlmostEqual(spin71.kex/1000, 2438.20525930405/1000, 4) 
4768          self.assertAlmostEqual(spin71.chi2, 15.1644913030633, 4) 
4769   
4770          # Test the conversion to k_AB from kex and pA. 
4771          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4772          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4773   
4774          # Test the conversion to k_BA from kex and pA. 
4775          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4776          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4777   
4778   
4779 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_star(self): 
4780          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star' dispersion model. 
4781   
4782          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4783          """ 
4784   
4785          # Base data setup. 
4786          self.setup_hansen_cpmg_data(model='NS CPMG 2-site star') 
4787   
4788          # Alias the spins. 
4789          spin70 = return_spin(":70") 
4790          spin71 = return_spin(":71") 
4791   
4792          # The R20 keys. 
4793          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4794          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4795   
4796          # Set the initial parameter values. 
4797          spin70.r2 = {r20_key1: 6.996327746, r20_key2: 9.452051268} 
4798          spin70.pA = 0.9897519798 
4799          spin70.dw = 5.644862195 
4800          spin70.kex = 1723.820567 
4801          spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 
4802          spin71.pA = 0.9968032899 
4803          spin71.dw = 4.577891393 
4804          spin71.kex = 1830.044597 
4805   
4806          # Low precision optimisation. 
4807          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4808   
4809          # Printout. 
4810          print("\n\nOptimised parameters:\n") 
4811          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4812          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4813          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4814          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4815          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4816          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4817          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4818   
4819          # Checks for residue :70. 
4820          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95543947938561, 1) 
4821          self.assertAlmostEqual(spin70.r2[r20_key2], 9.38991914134929, 1) 
4822          self.assertAlmostEqual(spin70.pA, 0.989702750971153, 3) 
4823          self.assertAlmostEqual(spin70.dw, 5.67527122494516, 1) 
4824          self.assertAlmostEqual(spin70.kex/1000, 1715.72032391817/1000, 1) 
4825          self.assertAlmostEqual(spin70.chi2, 52.5011991483842, 1) 
4826   
4827          # Checks for residue :71. 
4828          self.assertAlmostEqual(spin71.r2[r20_key1], 4.992594256544, 1) 
4829          self.assertAlmostEqual(spin71.pA, 0.986716058519642, 2) 
4830          self.assertAlmostEqual(spin71.dw/100, 2.09292495350993/100, 2) 
4831          self.assertAlmostEqual(spin71.kex/100000, 2438.04423541463/100000, 2) 
4832          self.assertAlmostEqual(spin71.chi2/100, 15.1644902423334/100, 1) 
4833   
4834          # Test the conversion to k_AB from kex and pA. 
4835          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4836          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4837   
4838          # Test the conversion to k_BA from kex and pA. 
4839          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4840          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4841   
4842   
4843 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_star_full(self): 
4844          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star full' dispersion model. 
4845   
4846          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4847          """ 
4848   
4849          # Base data setup. 
4850          self.setup_hansen_cpmg_data(model='NS CPMG 2-site star full') 
4851   
4852          # Alias the spins. 
4853          spin70 = return_spin(":70") 
4854          spin71 = return_spin(":71") 
4855   
4856          # The R20 keys. 
4857          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4858          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4859   
4860          # Set the initial parameter values. 
4861          spin70.r2a = {r20_key1: 6.44836878645126, r20_key2: 7.00382877393494} 
4862          spin70.r2b = {r20_key1: 12.2083127421994, r20_key2: 199.862962628402} 
4863          spin70.pA = 0.987648082613451 
4864          spin70.dw = 5.30679853807572 
4865          spin70.kex = 2033.25380420666 
4866          spin71.r2a = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 
4867          spin71.r2b = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 
4868          spin71.pA = 0.992258541625787 
4869          spin71.dw = 2.75140650899058 
4870          spin71.kex = 2106.60885247431 
4871   
4872          # Low precision optimisation. 
4873          self.interpreter.minimise.calculate() 
4874   
4875          # Checks for residue :70. 
4876          self.assertAlmostEqual(spin70.chi2/10, 45.773987568491123/10, 2) 
4877          self.assertAlmostEqual(spin71.chi2/10, 17.329385665659192/10, 2) 
4878   
4879   
4880 -    def test_hansen_cpmgfit_input(self): 
4881          """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CPMGFit. 
4882   
4883          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4884          """ 
4885   
4886          # Load the R2eff results file. 
4887          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 
4888          self.interpreter.results.read(file_name) 
4889          self.interpreter.deselect.spin(':4') 
4890   
4891          # Set up the model. 
4892          self.interpreter.relax_disp.select_model('LM63') 
4893   
4894          # Generate the input files. 
4895          self.interpreter.relax_disp.cpmgfit_input(force=True, dir=ds.tmpdir) 
4896   
4897          # What the files should contain. 
4898          batch_file = ['#! /bin/sh\n', '\n', 'cpmgfit -grid -xmgr -f spin_70_N.in | tee spin_70_N.out\n', 'cpmgfit -grid -xmgr -f spin_71_N.in | tee spin_71_N.out\n'] 
4899          spin1 = [ 
4900              "title :70@N\n", 
4901              "fields 2 11.7432964915 18.7892743865\n", 
4902              "function CPMG\n", 
4903              "R2 1 10 20\n", 
4904              "Rex 0 100.0 100\n", 
4905              "Tau 0 10.0 100\n", 
4906              "xmgr\n", 
4907              "@ xaxis label \"1/tcp (1/ms)\"\n", 
4908              "@ yaxis label \"R2(tcp) (rad/s)\"\n", 
4909              "@ xaxis ticklabel format decimal\n", 
4910              "@ yaxis ticklabel format decimal\n", 
4911              "@ xaxis ticklabel char size 0.8\n", 
4912              "@ yaxis ticklabel char size 0.8\n", 
4913              "@ world xmin 0.0\n", 
4914              "data\n", 
4915              "0.133333             16.045541            0.310925             11.743296           \n", 
4916              "0.266667             14.877925            0.303217             11.743296           \n", 
4917              "0.400000             14.357820            0.299894             11.743296           \n", 
4918              "0.533333             12.664495            0.289532             11.743296           \n", 
4919              "0.666667             12.363205            0.287760             11.743296           \n", 
4920              "0.800000             11.092532            0.280514             11.743296           \n", 
4921              "0.933333             10.566090            0.277619             11.743296           \n", 
4922              "1.066667             9.805807             0.273544             11.743296           \n", 
4923              "1.200000             9.564301             0.272276             11.743296           \n", 
4924              "1.333333             9.015634             0.269442             11.743296           \n", 
4925              "1.466667             8.607765             0.267375             11.743296           \n", 
4926              "1.600000             8.279997             0.265740             11.743296           \n", 
4927              "1.733333             8.474536             0.266708             11.743296           \n", 
4928              "1.866667             8.158973             0.265141             11.743296           \n", 
4929              "2.000000             7.988631             0.264304             11.743296           \n", 
4930              "0.133333             22.224914            0.166231             18.789274           \n", 
4931              "0.266667             21.230874            0.162377             18.789274           \n", 
4932              "0.400000             20.603704            0.160017             18.789274           \n", 
4933              "0.533333             20.327797            0.158996             18.789274           \n", 
4934              "0.666667             18.855377            0.153719             18.789274           \n", 
4935              "0.800000             18.537531            0.152617             18.789274           \n", 
4936              "0.933333             17.508069            0.149138             18.789274           \n", 
4937              "1.066667             16.035604            0.144391             18.789274           \n", 
4938              "1.200000             15.168192            0.141717             18.789274           \n", 
4939              "1.333333             14.431802            0.139516             18.789274           \n", 
4940              "1.466667             14.034137            0.138354             18.789274           \n", 
4941              "1.600000             12.920148            0.135192             18.789274           \n", 
4942              "1.733333             12.653673            0.134456             18.789274           \n", 
4943              "1.866667             12.610864            0.134338             18.789274           \n", 
4944              "2.000000             11.969303            0.132601             18.789274           \n" 
4945          ] 
4946          spin2 = [ 
4947              "title :71@N\n", 
4948              "fields 2 11.7432964915 18.7892743865\n", 
4949              "function CPMG\n", 
4950              "R2 1 10 20\n", 
4951              "Rex 0 100.0 100\n", 
4952              "Tau 0 10.0 100\n", 
4953              "xmgr\n", 
4954              "@ xaxis label \"1/tcp (1/ms)\"\n", 
4955              "@ yaxis label \"R2(tcp) (rad/s)\"\n", 
4956              "@ xaxis ticklabel format decimal\n", 
4957              "@ yaxis ticklabel format decimal\n", 
4958              "@ xaxis ticklabel char size 0.8\n", 
4959              "@ yaxis ticklabel char size 0.8\n", 
4960              "@ world xmin 0.0\n", 
4961              "data\n", 
4962              "0.133333             7.044342             0.170035             11.743296           \n", 
4963              "0.266667             6.781033             0.169228             11.743296           \n", 
4964              "0.400000             6.467623             0.168279             11.743296           \n", 
4965              "0.533333             6.333340             0.167876             11.743296           \n", 
4966              "0.666667             6.323238             0.167846             11.743296           \n", 
4967              "0.800000             6.005245             0.166902             11.743296           \n", 
4968              "0.933333             5.767052             0.166203             11.743296           \n", 
4969              "1.066667             5.476968             0.165361             11.743296           \n", 
4970              "1.200000             5.469949             0.165341             11.743296           \n", 
4971              "1.333333             5.295113             0.164838             11.743296           \n", 
4972              "1.466667             5.435648             0.165242             11.743296           \n", 
4973              "1.600000             5.410400             0.165169             11.743296           \n", 
4974              "1.733333             5.437554             0.165247             11.743296           \n", 
4975              "1.866667             5.176844             0.164501             11.743296           \n", 
4976              "2.000000             5.227232             0.164644             11.743296           \n", 
4977              "0.133333             11.530903            0.081928             18.789274           \n", 
4978              "0.266667             10.983094            0.081041             18.789274           \n", 
4979              "0.400000             10.512403            0.080294             18.789274           \n", 
4980              "0.533333             9.984805             0.079473             18.789274           \n", 
4981              "0.666667             9.573163             0.078845             18.789274           \n", 
4982              "0.800000             9.178810             0.078253             18.789274           \n", 
4983              "0.933333             8.935719             0.077893             18.789274           \n", 
4984              "1.066667             8.610147             0.077416             18.789274           \n", 
4985              "1.200000             8.353778             0.077045             18.789274           \n", 
4986              "1.333333             8.173729             0.076787             18.789274           \n", 
4987              "1.466667             8.091607             0.076670             18.789274           \n", 
4988              "1.600000             7.706420             0.076126             18.789274           \n", 
4989              "1.733333             7.709125             0.076129             18.789274           \n", 
4990              "1.866667             7.610856             0.075992             18.789274           \n", 
4991              "2.000000             7.552584             0.075911             18.789274           \n", 
4992          ] 
4993   
4994          # Check the batch file. 
4995          print("\nChecking the batch file.") 
4996          file = open("%s%sbatch_run.sh" % (ds.tmpdir, sep)) 
4997          lines = file.readlines() 
4998          file.close() 
4999          for i in range(len(lines)): 
5000              self.assertEqual(batch_file[i], lines[i]) 
5001   
5002          # Check spin :70@N. 
5003          print("\nChecking the spin :70@N input file.") 
5004          file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_70_N')) 
5005          lines = file.readlines() 
5006          file.close() 
5007          for i in range(len(spin1)): 
5008              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
5009          for i in range(len(lines)): 
5010              self.assertEqual(spin1[i], lines[i]) 
5011   
5012          # Check spin :71@N. 
5013          print("\nChecking the spin :71@N input file.") 
5014          file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_71_N')) 
5015          lines = file.readlines() 
5016          file.close() 
5017          for i in range(len(lines)): 
5018              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
5019          for i in range(len(spin2)): 
5020              self.assertEqual(spin2[i], lines[i]) 
5021   
5022   
5023 -    def test_korzhnev_2005_15n_dq_data(self): 
5024          """Optimisation of the Korzhnev et al., 2005 15N DQ CPMG data using the 'NS MMQ 2-site' model. 
5025   
5026          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5027   
5028          Here only the 15N DQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5029   
5030              - r2 = {'500': 9.487269007171426, '600': 11.718267257562591, '800': 13.624551743116887}, 
5031              - pA = 0.965402506690231, 
5032              - dw = 0.805197170133360, 
5033              - dwH = -0.595536627771890, 
5034              - kex = 569.003663067619868, 
5035              - chi2 = 9.297671357952812. 
5036          """ 
5037   
5038          # Base data setup. 
5039          self.setup_korzhnev_2005_data(data_list=['DQ']) 
5040   
5041          # Alias the spin. 
5042          spin = return_spin(":9@N") 
5043   
5044          # The R20 keys. 
5045          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5046          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5047          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5048   
5049          # Set the initial parameter values. 
5050          spin.r2 = {r20_key1: 9.48527908326952, r20_key2: 11.7135951595536, r20_key3: 13.6153887849344} 
5051          spin.pA = 0.965638501551899 
5052          spin.dw = 2.8537583461577 
5053          spin.dwH = -0.387633062766635 
5054          spin.kex = 573.704033851592 
5055   
5056          # Low precision optimisation. 
5057          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5058   
5059          # Monte Carlo simulations. 
5060          self.interpreter.monte_carlo.setup(number=3) 
5061          self.interpreter.monte_carlo.create_data(method='back_calc') 
5062          self.interpreter.monte_carlo.initial_values() 
5063          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5064          self.interpreter.monte_carlo.error_analysis() 
5065   
5066          # Plot the dispersion curves. 
5067          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5068   
5069          # Save the results. 
5070          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5071   
5072          # Printout. 
5073          print("\n\nOptimised parameters:\n") 
5074          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5075          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5076          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5077          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5078          print("%-20s %20.15g" % ("pA", spin.pA)) 
5079          print("%-20s %20.15g" % ("dw", spin.dw)) 
5080          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5081          print("%-20s %20.15g" % ("kex", spin.kex)) 
5082          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5083   
5084          # Checks for residue :9. 
5085          self.assertAlmostEqual(spin.r2[r20_key1], 9.4870656457415, 2) 
5086          self.assertAlmostEqual(spin.r2[r20_key2], 11.7183291788929, 2) 
5087          self.assertAlmostEqual(spin.r2[r20_key3], 13.6241729933153, 2) 
5088          self.assertAlmostEqual(spin.pA, 0.965405468217295, 4) 
5089          self.assertAlmostEqual(spin.dw, 2.76835528427355, 1) 
5090          self.assertAlmostEqual(spin.dwH, -0.396489341086363, 2) 
5091          self.assertAlmostEqual(spin.kex/1000, 569.06937047601/1000, 3) 
5092          self.assertAlmostEqual(spin.chi2, 9.29767487125257, 2) 
5093   
5094   
5095 -    def test_korzhnev_2005_15n_mq_data(self): 
5096          """Optimisation of the Korzhnev et al., 2005 15N MQ CPMG data using the 'NS MMQ 2-site' model. 
5097   
5098          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5099   
5100          Here only the 15N MQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5101   
5102              - r2 = {'500': 5.993083514798655, '600': 6.622184438384841, '800': 8.640765919352019}, 
5103              - pA = 0.930027999814003, 
5104              - dw = 4.338620619954370, 
5105              - dwH = -0.274250775560818, 
5106              - kex = 344.613362916544475, 
5107              - chi2 = 10.367733168217050. 
5108          """ 
5109   
5110          # Base data setup. 
5111          self.setup_korzhnev_2005_data(data_list=['MQ']) 
5112   
5113          # Alias the spin. 
5114          spin = return_spin(":9@N") 
5115   
5116          # The R20 keys. 
5117          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5118          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5119          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5120   
5121          # Set the initial parameter values. 
5122          spin.r2 = {r20_key1: 6.02016436619016, r20_key2: 6.65421500772308, r20_key3: 8.6729591487622} 
5123          spin.pA = 0.930083249288083 
5124          spin.dw = 4.33890689462363 
5125          spin.dwH = -0.274316585638047 
5126          spin.kex = 344.329651956132 
5127   
5128          # Low precision optimisation. 
5129          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5130   
5131          # Monte Carlo simulations. 
5132          self.interpreter.monte_carlo.setup(number=3) 
5133          self.interpreter.monte_carlo.create_data(method='back_calc') 
5134          self.interpreter.monte_carlo.initial_values() 
5135          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5136          self.interpreter.monte_carlo.error_analysis() 
5137   
5138          # Plot the dispersion curves. 
5139          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5140   
5141          # Save the results. 
5142          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5143   
5144          # Printout. 
5145          print("\n\nOptimised parameters:\n") 
5146          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5147          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5148          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5149          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5150          print("%-20s %20.15g" % ("pA", spin.pA)) 
5151          print("%-20s %20.15g" % ("dw", spin.dw)) 
5152          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5153          print("%-20s %20.15g" % ("kex", spin.kex)) 
5154          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5155   
5156          # Checks for residue :9. 
5157          self.assertAlmostEqual(spin.r2[r20_key1], 5.99503641023038, 1) 
5158          self.assertAlmostEqual(spin.r2[r20_key2], 6.62432897608527, 1) 
5159          self.assertAlmostEqual(spin.r2[r20_key3], 8.64278915809492, 1) 
5160          self.assertAlmostEqual(spin.pA, 0.930036474040713, 3) 
5161          self.assertAlmostEqual(spin.dw, 4.33848403058432, 2) 
5162          self.assertAlmostEqual(spin.dwH, -0.274246558825267, 3) 
5163          self.assertAlmostEqual(spin.kex/1000, 344.626563267384/1000, 3) 
5164          self.assertAlmostEqual(spin.chi2, 10.3677362372789, 2) 
5165   
5166   
5167 -    def test_korzhnev_2005_15n_sq_data(self): 
5168          """Optimisation of the Korzhnev et al., 2005 15N SQ CPMG data using the 'NS MMQ 2-site' model. 
5169   
5170          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5171   
5172          Here only the 15N SQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5173   
5174              - r2 = {'500': 8.335037972570017, '600': 8.761366016417508, '800': 10.225001019091822}, 
5175              - pA = 0.950003458294991, 
5176              - dw = 4.358402855315123, 
5177              - kex = 429.906473361926999, 
5178              - chi2 = 17.393331915567252. 
5179          """ 
5180   
5181          # Base data setup. 
5182          self.setup_korzhnev_2005_data(data_list=['SQ']) 
5183   
5184          # Alias the spin. 
5185          spin = return_spin(":9@N") 
5186   
5187          # The R20 keys. 
5188          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5189          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5190          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5191   
5192          # Set the initial parameter values. 
5193          spin.r2 = {r20_key1: 8.334232330326190, r20_key2: 8.756773997879968, r20_key3: 10.219320492033058} 
5194          spin.pA = 0.950310172115387 
5195          spin.dw = 4.356737157889636 
5196          spin.kex = 433.176323890829849 
5197   
5198          # Low precision optimisation. 
5199          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5200   
5201          # Monte Carlo simulations. 
5202          self.interpreter.monte_carlo.setup(number=3) 
5203          self.interpreter.monte_carlo.create_data(method='back_calc') 
5204          self.interpreter.monte_carlo.initial_values() 
5205          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5206          self.interpreter.monte_carlo.error_analysis() 
5207   
5208          # Plot the dispersion curves. 
5209          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5210   
5211          # Save the results. 
5212          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5213   
5214          # Printout. 
5215          print("\n\nOptimised parameters:\n") 
5216          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5217          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5218          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5219          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5220          print("%-20s %20.15g" % ("pA", spin.pA)) 
5221          print("%-20s %20.15g" % ("dw", spin.dw)) 
5222          print("%-20s %20.15g" % ("kex", spin.kex)) 
5223          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5224   
5225          # Checks for residue :9. 
5226          self.assertAlmostEqual(spin.r2[r20_key1], 8.33499994313902, 2) 
5227          self.assertAlmostEqual(spin.r2[r20_key2], 8.76118738798082, 2) 
5228          self.assertAlmostEqual(spin.r2[r20_key3], 10.2250821829928, 1) 
5229          self.assertAlmostEqual(spin.pA, 0.950000281516303, 3) 
5230          self.assertAlmostEqual(spin.dw, 4.35845318983581, 2) 
5231          self.assertAlmostEqual(spin.kex/1000, 429.874510184149/1000, 2) 
5232          self.assertAlmostEqual(spin.chi2, 17.3933357984425, 1) 
5233   
5234   
5235 -    def test_korzhnev_2005_15n_zq_data(self): 
5236          """Optimisation of the Korzhnev et al., 2005 15N ZQ CPMG data using the 'NS MMQ 2-site' model. 
5237   
5238          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5239   
5240          Here only the 15N ZQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5241   
5242              - r2 = {'500': 5.909812628572937, '600': 6.663690132557320, '800': 6.787171647689906}, 
5243              - pA = 0.942452612380140, 
5244              - dw = 0.858972784230892, 
5245              - dwH = 0.087155962730608, 
5246              - kex = 373.219151384798920, 
5247              - chi2 = 23.863208106025152. 
5248          """ 
5249   
5250          # Base data setup. 
5251          self.setup_korzhnev_2005_data(data_list=['ZQ']) 
5252   
5253          # Alias the spin. 
5254          spin = return_spin(":9@N") 
5255   
5256          # The R20 keys. 
5257          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5258          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5259          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5260   
5261          # Set the initial parameter values. 
5262          spin.r2 = {r20_key1: 5.91033272691614, r20_key2: 6.66368695342258, r20_key3: 6.78922219135537} 
5263          spin.pA = 0.942457332074014 
5264          spin.dw = 0.850592422908884 
5265          spin.dwH = 0.0881272284455416 
5266          spin.kex = 372.745483351305 
5267   
5268          # Low precision optimisation. 
5269          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5270   
5271          # Monte Carlo simulations. 
5272          self.interpreter.monte_carlo.setup(number=3) 
5273          self.interpreter.monte_carlo.create_data(method='back_calc') 
5274          self.interpreter.monte_carlo.initial_values() 
5275          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5276          self.interpreter.monte_carlo.error_analysis() 
5277   
5278          # Plot the dispersion curves. 
5279          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5280   
5281          # Save the results. 
5282          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5283   
5284          # Printout. 
5285          print("\n\nOptimised parameters:\n") 
5286          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5287          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5288          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5289          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5290          print("%-20s %20.15g" % ("pA", spin.pA)) 
5291          print("%-20s %20.15g" % ("dw", spin.dw)) 
5292          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5293          print("%-20s %20.15g" % ("kex", spin.kex)) 
5294          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5295   
5296          # Checks for residue :9. 
5297          self.assertAlmostEqual(spin.r2[r20_key1], 5.9098385837035, 2) 
5298          self.assertAlmostEqual(spin.r2[r20_key2], 6.66377885876553, 2) 
5299          self.assertAlmostEqual(spin.r2[r20_key3], 6.78717432941353, 2) 
5300          self.assertAlmostEqual(spin.pA, 0.942457141344462, 4) 
5301          self.assertAlmostEqual(spin.dw, 0.84442055695814, 1) 
5302          self.assertAlmostEqual(spin.dwH, 0.0886367674566058, 2) 
5303          self.assertAlmostEqual(spin.kex/1000, 373.243053643367/1000, 3) 
5304          self.assertAlmostEqual(spin.chi2, 23.863211604121, 1) 
5305   
5306   
5307 -    def test_korzhnev_2005_1h_mq_data(self): 
5308          """Optimisation of the Korzhnev et al., 2005 1H MQ CPMG data using the 'NS MMQ 2-site' model. 
5309   
5310          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5311   
5312          Here only the 1H MQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5313   
5314              - r2 = {'500': -0.000016676911302, '600': 0.036594127620440, '800': 2.131014839635728}, 
5315              - pA = 0.936911090448340, 
5316              - dw = 4.325314846914845, 
5317              - dwH = -0.213870168665628, 
5318              - kex = 487.361914835074117, 
5319              - chi2 = 14.870371897291138. 
5320          """ 
5321   
5322          # Base data setup. 
5323          self.setup_korzhnev_2005_data(data_list=['1H MQ']) 
5324   
5325          # Alias the spin. 
5326          spin = return_spin(":9@N") 
5327   
5328          # The R20 keys. 
5329          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5330          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5331          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5332   
5333          # Set the initial parameter values. 
5334          spin.r2 = {r20_key1: 0.000022585022901, r20_key2: 0.039223196112941, r20_key3: 2.136576686700357} 
5335          spin.pA = 0.936884348941701 
5336          spin.dw = 4.326454531583964 
5337          spin.dwH = -0.214026093221782 
5338          spin.kex = 487.043592705469223 
5339   
5340          # Low precision optimisation. 
5341          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=100) 
5342   
5343          # Monte Carlo simulations. 
5344          self.interpreter.monte_carlo.setup(number=3) 
5345          self.interpreter.monte_carlo.create_data(method='back_calc') 
5346          self.interpreter.monte_carlo.initial_values() 
5347          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5348          self.interpreter.monte_carlo.error_analysis() 
5349   
5350          # Plot the dispersion curves. 
5351          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5352   
5353          # Save the results. 
5354          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5355   
5356          # Printout. 
5357          print("\n\nOptimised parameters:\n") 
5358          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5359          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5360          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5361          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5362          print("%-20s %20.15g" % ("pA", spin.pA)) 
5363          print("%-20s %20.15g" % ("dw", spin.dw)) 
5364          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5365          print("%-20s %20.15g" % ("kex", spin.kex)) 
5366          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5367   
5368          # Checks for residue :9. 
5369          self.assertAlmostEqual(spin.r2[r20_key1], 2.48493199969936e-05, 4) 
5370          self.assertAlmostEqual(spin.r2[r20_key2], 0.0382382195911849, 2) 
5371          self.assertAlmostEqual(spin.r2[r20_key3], 2.13397221524655, 2) 
5372          self.assertAlmostEqual(spin.pA, 0.936879359956996, 4) 
5373          self.assertAlmostEqual(spin.dw, 4.32573362253701, 2) 
5374          self.assertAlmostEqual(spin.dwH, -0.213951762275293, 2) 
5375          self.assertAlmostEqual(spin.kex/1000, 487.021196851596/1000, 4) 
5376          self.assertAlmostEqual(spin.chi2, 14.8704048958378, 2) 
5377   
5378   
5379 -    def test_korzhnev_2005_1h_sq_data(self): 
5380          """Optimisation of the Korzhnev et al., 2005 1H SQ CPMG data using the 'NS MMQ 2-site' model. 
5381   
5382          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5383   
5384          Here only the 1H SQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5385   
5386              - r2 = {'500': 6.691697587650816, '600': 6.998915158708793, '800': 5.519267837559072}, 
5387              - pA = 0.946949480545876, 
5388              - dwH = -0.265279672133308, 
5389              - kex = 406.548178869750700, 
5390              - chi2 = 50.400680290545026. 
5391          """ 
5392   
5393          # Base data setup. 
5394          self.setup_korzhnev_2005_data(data_list=['1H SQ']) 
5395   
5396          # Alias the spin. 
5397          spin = return_spin(":9@N") 
5398   
5399          # The R20 keys. 
5400          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5401          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5402          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5403   
5404          # Set the initial parameter values. 
5405          spin.r2 = {r20_key1: 6.69107911078939, r20_key2: 6.99888898689085, r20_key3: 5.52012880268077} 
5406          spin.pA = 0.946990967372467 
5407          spin.dwH = -0.265308128403529 
5408          spin.kex = 406.843250675648 
5409   
5410          # Low precision optimisation. 
5411          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5412   
5413          # Monte Carlo simulations. 
5414          self.interpreter.monte_carlo.setup(number=3) 
5415          self.interpreter.monte_carlo.create_data(method='back_calc') 
5416          self.interpreter.monte_carlo.initial_values() 
5417          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5418          self.interpreter.monte_carlo.error_analysis() 
5419   
5420          # Plot the dispersion curves. 
5421          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5422   
5423          # Save the results. 
5424          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5425   
5426          # Printout. 
5427          print("\n\nOptimised parameters:\n") 
5428          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5429          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5430          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5431          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5432          print("%-20s %20.15g" % ("pA", spin.pA)) 
5433          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5434          print("%-20s %20.15g" % ("kex", spin.kex)) 
5435          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5436   
5437          # Checks for residue :9. 
5438          self.assertAlmostEqual(spin.r2[r20_key1], 6.69168251154302, 2) 
5439          self.assertAlmostEqual(spin.r2[r20_key2], 6.99900388754043, 2) 
5440          self.assertAlmostEqual(spin.r2[r20_key3], 5.51921590064843, 2) 
5441          self.assertAlmostEqual(spin.pA, 0.946951877648819, 4) 
5442          self.assertAlmostEqual(spin.dwH, -0.265280175525516, 3) 
5443          self.assertAlmostEqual(spin.kex/1000, 406.566453278183/1000, 2) 
5444          self.assertAlmostEqual(spin.chi2, 50.4006836222044, 1) 
5445   
5446   
5447 -    def test_korzhnev_2005_all_data(self): 
5448          """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 
5449   
5450          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5451   
5452          Here all data will be optimised.  The values found by cpmg_fit using just this data are: 
5453   
5454              - r2 = {'H-S 500':  6.671649051677150, 'H-S 600':  6.988634195648529, 'H-S 800':  5.527971316790596, 
5455                      'N-S 500':  8.394988400015988, 'N-S 600':  8.891359568401835, 'N-S 800': 10.405356669006709, 
5456                      'NHZ 500':  5.936446687394352, 'NHZ 600':  6.717058062814535, 'NHZ 800':  6.838733853403030, 
5457                      'NHD 500':  8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 
5458                      'HNM 500':  7.851325614877817, 'HNM 600':  8.408803624020202, 'HNM 800': 11.227489645758979, 
5459                      'NHM 500':  9.189159145380575, 'NHM 600':  9.856814478405868, 'NHM 800': 11.967910041807118}, 
5460              - pA = 0.943125351763911, 
5461              - dw = 4.421827493809807, 
5462              - dwH = -0.272637034755752, 
5463              - kex = 360.609744568697238, 
5464              - chi2 = 162.589570340050813. 
5465          """ 
5466   
5467          # Base data setup. 
5468          self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 
5469   
5470          # Alias the spin. 
5471          spin = return_spin(":9@N") 
5472   
5473          # The R20 keys. 
5474          r20_key1  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5475          r20_key2  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5476          r20_key3  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5477          r20_key4  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5478          r20_key5  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5479          r20_key6  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5480          r20_key7  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5481          r20_key8  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5482          r20_key9  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5483          r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5484          r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5485          r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5486          r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5487          r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5488          r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5489          r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5490          r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5491          r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5492   
5493          # Set the initial parameter values. 
5494          spin.r2 = { 
5495              r20_key1:   6.67288025927458, r20_key2:   6.98951408255098, r20_key3:   5.52959273852704, 
5496              r20_key4:   8.39471048876782, r20_key5:   8.89290699178799, r20_key6:  10.40770687236930, 
5497              r20_key7:   5.93611174376373, r20_key8:   6.71735669582514, r20_key9:   6.83835225518265, 
5498              r20_key10:  8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 
5499              r20_key13:  7.85956711501608, r20_key14:  8.41891642907918, r20_key15: 11.23620892230380, 
5500              r20_key16:  9.19654863789350, r20_key17:  9.86031627358462, r20_key18: 11.97523755925750 
5501          } 
5502          spin.pA = 0.943129019477673 
5503          spin.dw = 4.42209952545181 
5504          spin.dwH = -0.27258970590969 
5505          spin.kex = 360.516132791038 
5506   
5507          # Low precision optimisation. 
5508          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=10) 
5509   
5510          # Monte Carlo simulations. 
5511          self.interpreter.monte_carlo.setup(number=3) 
5512          self.interpreter.monte_carlo.create_data(method='back_calc') 
5513          self.interpreter.monte_carlo.initial_values() 
5514          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5515          self.interpreter.monte_carlo.error_analysis() 
5516   
5517          # Plot the dispersion curves. 
5518          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5519   
5520          # Save the results. 
5521          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5522   
5523          # Printout. 
5524          print("\n\nOptimised parameters:\n") 
5525          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5526          print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 
5527          print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 
5528          print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 
5529          print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 
5530          print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 
5531          print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 
5532          print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 
5533          print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 
5534          print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 
5535          print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 
5536          print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 
5537          print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 
5538          print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 
5539          print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 
5540          print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 
5541          print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 
5542          print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 
5543          print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 
5544          print("%-20s %20.15g" % ("pA", spin.pA)) 
5545          print("%-20s %20.15g" % ("dw", spin.dw)) 
5546          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5547          print("%-20s %20.15g" % ("kex", spin.kex)) 
5548          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5549   
5550          # Checks for residue :9. 
5551          self.assertAlmostEqual(spin.r2[r20_key1],  6.67288025927458, 4) 
5552          self.assertAlmostEqual(spin.r2[r20_key2],  6.98951408255098, 4) 
5553          self.assertAlmostEqual(spin.r2[r20_key3],  5.52959273852704, 4) 
5554          self.assertAlmostEqual(spin.r2[r20_key4],  8.39471048876782, 4) 
5555          self.assertAlmostEqual(spin.r2[r20_key5],  8.89290699178799, 4) 
5556          self.assertAlmostEqual(spin.r2[r20_key6],  10.4077068723693, 4) 
5557          self.assertAlmostEqual(spin.r2[r20_key7],  5.93611174376373, 4) 
5558          self.assertAlmostEqual(spin.r2[r20_key8],  6.71735669582514, 4) 
5559          self.assertAlmostEqual(spin.r2[r20_key9],  6.83835225518265, 4) 
5560          self.assertAlmostEqual(spin.r2[r20_key10], 8.59615074668922, 4) 
5561          self.assertAlmostEqual(spin.r2[r20_key11], 10.6512137889291, 4) 
5562          self.assertAlmostEqual(spin.r2[r20_key12], 12.5710822919109, 4) 
5563          self.assertAlmostEqual(spin.r2[r20_key13], 7.85956711501608, 4) 
5564          self.assertAlmostEqual(spin.r2[r20_key14], 8.41891642907918, 4) 
5565          self.assertAlmostEqual(spin.r2[r20_key15], 11.2362089223038, 4) 
5566          self.assertAlmostEqual(spin.r2[r20_key16], 9.1965486378935, 4) 
5567          self.assertAlmostEqual(spin.r2[r20_key17], 9.86031627358462, 4) 
5568          self.assertAlmostEqual(spin.r2[r20_key18], 11.9752375592575, 4) 
5569          self.assertAlmostEqual(spin.pA, 0.943129019477673, 4) 
5570          self.assertAlmostEqual(spin.dw, 4.42209952545181, 4) 
5571          self.assertAlmostEqual(spin.dwH, -0.27258970590969, 4) 
5572          self.assertAlmostEqual(spin.kex/1000, 360.516132791038/1000, 4) 
5573          self.assertAlmostEqual(spin.chi2/1000, 162.596331278669/1000, 3) 
5574   
5575   
5576 -    def test_korzhnev_2005_all_data_disp_speed_bug(self): 
5577          """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 
5578   
5579          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5580   
5581          Here all data will be optimised.  The values found by cpmg_fit using just this data are: 
5582   
5583              - r2 = {'H-S 500':  6.671649051677150, 'H-S 600':  6.988634195648529, 'H-S 800':  5.527971316790596, 
5584                      'N-S 500':  8.394988400015988, 'N-S 600':  8.891359568401835, 'N-S 800': 10.405356669006709, 
5585                      'NHZ 500':  5.936446687394352, 'NHZ 600':  6.717058062814535, 'NHZ 800':  6.838733853403030, 
5586                      'NHD 500':  8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 
5587                      'HNM 500':  7.851325614877817, 'HNM 600':  8.408803624020202, 'HNM 800': 11.227489645758979, 
5588                      'NHM 500':  9.189159145380575, 'NHM 600':  9.856814478405868, 'NHM 800': 11.967910041807118}, 
5589              - pA = 0.943125351763911, 
5590              - dw = 4.421827493809807, 
5591              - dwH = -0.272637034755752, 
5592              - kex = 360.609744568697238, 
5593              - chi2 = 162.589570340050813. 
5594          """ 
5595   
5596          # Base data setup. 
5597          self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 
5598   
5599          # Alias the spin. 
5600          spin = return_spin(":9@N") 
5601   
5602          # The R20 keys. 
5603          r20_key1  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5604          r20_key2  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5605          r20_key3  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5606          r20_key4  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5607          r20_key5  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5608          r20_key6  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5609          r20_key7  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5610          r20_key8  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5611          r20_key9  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5612          r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5613          r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5614          r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5615          r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5616          r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5617          r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5618          r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5619          r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5620          r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5621   
5622          # Set the initial parameter values. 
5623          spin.r2 = { 
5624              r20_key1:   6.67288025927458, r20_key2:   6.98951408255098, r20_key3:   5.52959273852704, 
5625              r20_key4:   8.39471048876782, r20_key5:   8.89290699178799, r20_key6:  10.40770687236930, 
5626              r20_key7:   5.93611174376373, r20_key8:   6.71735669582514, r20_key9:   6.83835225518265, 
5627              r20_key10:  8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 
5628              r20_key13:  7.85956711501608, r20_key14:  8.41891642907918, r20_key15: 11.23620892230380, 
5629              r20_key16:  9.19654863789350, r20_key17:  9.86031627358462, r20_key18: 11.97523755925750 
5630          } 
5631          spin.pA = 0.943129019477673 
5632          spin.dw = 4.42209952545181 
5633          spin.dwH = -0.27258970590969 
5634          spin.kex = 360.516132791038 
5635   
5636          # Calc the chi2 values at these parameters. 
5637          self.interpreter.minimise.calculate(verbosity=1) 
5638   
5639          # Printout. 
5640          print("\n\nOptimised parameters:\n") 
5641          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5642          print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 
5643          print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 
5644          print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 
5645          print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 
5646          print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 
5647          print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 
5648          print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 
5649          print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 
5650          print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 
5651          print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 
5652          print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 
5653          print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 
5654          print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 
5655          print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 
5656          print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 
5657          print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 
5658          print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 
5659          print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 
5660          print("%-20s %20.15g" % ("pA", spin.pA)) 
5661          print("%-20s %20.15g" % ("dw", spin.dw)) 
5662          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5663          print("%-20s %20.15g" % ("kex", spin.kex)) 
5664          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5665   
5666          # Checks for residue :9. 
5667          self.assertAlmostEqual(spin.chi2/1000, 162.511988511609/1000, 3) 
5668   
5669   
5670 -    def test_kteilum_fmpoulsen_makke_check_graphs(self): 
5671          """Check of all possible dispersion graphs from optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5672   
5673          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5674   
5675          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 
5676   
5677            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5678            - 0.483 0.89623903 2.4503699912708878 
5679            - 0.545 1.1694838 
5680            - 0.545 1.1761503 
5681            - 0.622 1.294 
5682            - 0.669 1.5176493 
5683            - 0.722 1.6238791 
5684            - 0.813 1.9395758 
5685            - 1.011 2.3558415 10.547000429321157 
5686          """ 
5687   
5688          # Base data setup. 
5689          model = 'TSMFK01' 
5690          expfolder = "acbp_cpmg_disp_048MGuHCl_40C_041223" 
5691          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model=model, expfolder=expfolder) 
5692   
5693          # Alias the spins. 
5694          res61L = cdp.mol[0].res[0].spin[0] 
5695   
5696          # The R20 keys. 
5697          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5698   
5699          # Set the initial parameter values. 
5700          res61L.r2a = {r20_key1: 8.0} 
5701          res61L.dw = 6.5 
5702          res61L.k_AB = 2.5 
5703   
5704          # Low precision optimisation. 
5705          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5706   
5707          # Start testing all possible combinations of graphs. 
5708          y_axis_types = [Y_AXIS_R2_EFF, Y_AXIS_R2_R1RHO] 
5709          x_axis_types = [X_AXIS_DISP, X_AXIS_THETA, X_AXIS_W_EFF] 
5710          interpolate_types = [INTERPOLATE_DISP] 
5711   
5712          # Write to temp folder. 
5713          result_dir_name = ds.tmpdir 
5714          result_folders = [model] 
5715          spin_id = ":61@N" 
5716   
5717          # Loop through all possible combinations of y_axis, x_axis and interpolation. 
5718          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder+sep+'check_graphs' 
5719   
5720          for result_folder in result_folders: 
5721              for y_axis in y_axis_types: 
5722                  for x_axis in x_axis_types: 
5723                      for interpolate in interpolate_types: 
5724                          # Determine file name: 
5725                          file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
5726   
5727                          # Make the file name. 
5728                          file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
5729   
5730                          # Write the curves. 
5731                          dir = result_dir_name+sep+result_folder 
5732                          print("Plotting combination of %s, %s, %s"%(y_axis, x_axis, interpolate)) 
5733                          self.interpreter.relax_disp.plot_disp_curves(dir=dir, y_axis=y_axis, x_axis=x_axis, interpolate=interpolate, force=True) 
5734   
5735                          # Get the file path. 
5736                          file_path = get_file_path(file_name, dir) 
5737   
5738                          # Test the plot file exists. 
5739                          print("Testing file access to graph: %s"%file_path) 
5740                          self.assert_(access(file_path, F_OK)) 
5741   
5742                          # Now open, and compare content, line by line. 
5743                          file_prod = open(file_path) 
5744                          lines_prod = file_prod.readlines() 
5745                          file_prod.close() 
5746   
5747                          # Define file to compare against. 
5748                          dir_comp = data_path+sep+result_folder 
5749                          file_path_comp = get_file_path(file_name, dir_comp) 
5750                          file_comp = open(file_path_comp) 
5751                          lines_comp = file_comp.readlines() 
5752                          file_comp.close() 
5753   
5754                          ## Assert number of lines is equal. 
5755                          self.assertEqual(len(lines_prod), len(lines_comp)) 
5756                          for j in range(len(lines_prod)): 
5757                              # Make the string test 
5758                              first_char = lines_prod[j][0] 
5759                              if first_char in ["@", "&"]: 
5760                                  self.assertEqual(lines_prod[j], lines_comp[j]) 
5761                              else: 
5762                                  # Split string in x, y, error. 
5763                                  # The error would change per run. 
5764                                  x_prod, y_prod, y_prod_err = lines_prod[j].split() 
5765                                  x_comp, y_comp, y_comp_err = lines_comp[j].split() 
5766                                  self.assertAlmostEqual(float(x_prod), float(x_comp)) 
5767                                  self.assertAlmostEqual(float(y_prod), float(y_comp)) 
5768                                  self.assertAlmostEqual(float(y_prod_err), float(y_comp_err)) 
5769   
5770   
5771 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72(self): 
5772          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5773   
5774          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5775          """ 
5776   
5777          # Base data setup. 
5778          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5779   
5780          # Alias the spins. 
5781          res61L = cdp.mol[0].res[0].spin[0] 
5782   
5783          # The R20 keys. 
5784          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5785   
5786          # Set the initial parameter values. 
5787          res61L.r2 = {r20_key1: 8.0} 
5788          res61L.pA = 0.9 
5789          res61L.dw = 6.0 
5790          res61L.kex = 600.0 
5791   
5792          # Low precision optimisation. 
5793          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5794   
5795          # Printout. 
5796          print("\n\nOptimised parameters:\n") 
5797          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5798          print("%-20s %20.15g" % ("R2 (600 MHz)", res61L.r2[r20_key1])) 
5799          print("%-20s %20.15g" % ("pA", res61L.pA)) 
5800          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5801          print("%-20s %20.15g" % ("kex", res61L.kex)) 
5802          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5803   
5804          # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 
5805          self.assertAlmostEqual(res61L.r2[r20_key1], 8.69277980194016, 4) 
5806          self.assertAlmostEqual(res61L.pA, 0.9943781590842946, 5) 
5807          self.assertAlmostEqual(res61L.dw, 6.389453131263374, 3) 
5808          self.assertAlmostEqual(res61L.kex, 609.262167216419, 0) 
5809          self.assertAlmostEqual(res61L.chi2, 65.99987828889657, 5) 
5810   
5811          # Test the conversion to k_AB from kex and pA. 
5812          self.assertEqual(res61L.k_AB, res61L.kex * (1.0 - res61L.pA)) 
5813   
5814          # Test the conversion to k_BA from kex and pA. 
5815          self.assertEqual(res61L.k_BA, res61L.kex * res61L.pA) 
5816   
5817   
5818 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72_full(self): 
5819          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5820   
5821          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5822          """ 
5823   
5824          # Base data setup. 
5825          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72 full', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5826   
5827          # Alias the spins. 
5828          res61L = cdp.mol[0].res[0].spin[0] 
5829   
5830          # The R20 keys. 
5831          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5832   
5833          # Set the initial parameter values. 
5834          res61L.r2a = {r20_key1: 8.0} 
5835          res61L.r2b = {r20_key1: 105.0} 
5836          res61L.pA = 0.9 
5837          res61L.dw = 6.0 
5838          res61L.kex = 500.0 
5839   
5840          # Low precision optimisation. 
5841          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5842   
5843          # Printout. 
5844          print("\n\nOptimised parameters:\n") 
5845          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5846          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5847          print("%-20s %20.15g" % ("R2B (600 MHz)", res61L.r2b[r20_key1])) 
5848          print("%-20s %20.15g" % ("pA", res61L.pA)) 
5849          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5850          print("%-20s %20.15g" % ("kex", res61L.kex)) 
5851          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5852   
5853          # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 
5854          self.assertAlmostEqual(res61L.r2a[r20_key1], 8.044428899438309, 0) 
5855          self.assertAlmostEqual(res61L.r2b[r20_key1], 105.11894506392449, -2) 
5856          self.assertAlmostEqual(res61L.pA, 0.992066883657578, 2) 
5857          self.assertAlmostEqual(res61L.dw, 6.389453586338883, 3) 
5858          self.assertAlmostEqual(res61L.kex, 513.483608742063, -2) 
5859          self.assertAlmostEqual(res61L.chi2, 65.99987828890289, 5) 
5860   
5861   
5862 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_tsmfk01(self): 
5863          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5864   
5865          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5866   
5867          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 
5868   
5869            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5870            - 0.483 0.89623903 2.4503699912708878 
5871            - 0.545 1.1694838 
5872            - 0.545 1.1761503 
5873            - 0.622 1.294 
5874            - 0.669 1.5176493 
5875            - 0.722 1.6238791 
5876            - 0.813 1.9395758 
5877            - 1.011 2.3558415 10.547000429321157 
5878          """ 
5879   
5880          # Base data setup. 
5881          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5882   
5883          # Alias the spins. 
5884          res61L = cdp.mol[0].res[0].spin[0] 
5885   
5886          # The R20 keys. 
5887          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5888   
5889          # Set the initial parameter values. 
5890          res61L.r2a = {r20_key1: 8.0} 
5891          res61L.dw = 6.5 
5892          res61L.k_AB = 2.5 
5893   
5894          # Low precision optimisation. 
5895          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5896   
5897          # Printout. 
5898          print("\n\nOptimised parameters:\n") 
5899          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5900          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5901          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5902          print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 
5903          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5904   
5905          # Checks for residue :61. Reference values from paper 
5906   
5907          self.assertAlmostEqual(res61L.k_AB, 2.45, 1) 
5908   
5909   
5910 -    def test_kteilum_fmpoulsen_makke_cpmg_data_101m_guhcl_to_tsmfk01(self): 
5911          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5912   
5913          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 1.01 M GuHCl (guanidine hydrochloride). 
5914   
5915          The comparison is to Figure 2, which is for dataset with 1 M GuHCl.  The reported results are expected to be in rad.s^-1.  Conversion into relax stored values is preferably. 
5916   
5917          Representative 15N CPMG relaxation dispersion curve measured on the cross peaks from residue L61 in folded ACBP at pH 5.3, 1 M GuHCl, and 40C: 
5918   
5919            1. The dotted line represents a residue-specific fit of all parameters in Eq. 1: 
5920              - k_AB = 11.3 +/- 0.7 s^-1, 
5921              - dw = (2.45 +/- 0.09) * 10^3 s^-1, 
5922              - R2 = 8.0 +/- 0.5 s^-1. 
5923   
5924            2. The solid line represents a global fit of k_AB to all protein residues and a residue-specific fit of dw and R2.: 
5925              - k_AB = 10.55 +/- 0.08 s^-1, 
5926              - dw = (2.44 +/- 0.08) * 10^3 s^-1, 
5927              - R2 = 8.4 +/- 0.3 s^-1. 
5928   
5929          Conversion of paper results to relax results is performed by: 
5930   
5931            - dw(ppm) = dw(rad.s^-1) * 10^6 * 1/(2*pi) * (gyro1H/(gyro15N*spectrometer_freq)) = 2.45E3 * 1E6 / (2 * math.pi) * (26.7522212E7/(-2.7126E7 * 599.8908622E6)) = -6.41 ppm. 
5932   
5933          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl.  The precise values are: 
5934   
5935            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5936            - 0.483 0.89623903 2.4503699912708878 
5937            - 0.545 1.1694838 
5938            - 0.545 1.1761503 
5939            - 0.622 1.294 
5940            - 0.669 1.5176493 
5941            - 0.722 1.6238791 
5942            - 0.813 1.9395758 
5943            - 1.011 2.3558415 10.547000429321157 
5944          """ 
5945   
5946          # Base data setup. 
5947          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_101MGuHCl_40C_041223") 
5948   
5949          # Alias the spins. 
5950          res61L = cdp.mol[0].res[0].spin[0] 
5951   
5952          # The R20 keys. 
5953          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086270e6) 
5954   
5955          # Set the initial parameter values. 
5956          res61L.r2a = {r20_key1: 8.0} 
5957          res61L.dw = 6.5 
5958          res61L.k_AB = 11.0 
5959   
5960          # Low precision optimisation. 
5961          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5962   
5963          # Printout. 
5964          print("\n\nOptimised parameters:\n") 
5965          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5966          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5967          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5968          print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 
5969          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5970   
5971          # Checks for residue :61. Reference values from paper 
5972   
5973          self.assertAlmostEqual(res61L.r2a[r20_key1], 8.4, 0) 
5974          self.assertAlmostEqual(res61L.dw, 6.41, 0) 
5975          self.assertAlmostEqual(res61L.k_AB, 10.55, 0) 
5976   
5977   
5978 -    def test_lm63_3site_synthetic(self): 
5979          """Test the 'LM63 3-site' dispersion model using the pure noise-free synthetic data.""" 
5980   
5981          # The path to the data files. 
5982          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'lm63_3site' 
5983   
5984          # Load the state file. 
5985          self.interpreter.reset() 
5986          self.interpreter.state.load(data_path+sep+'r2eff_values') 
5987   
5988          # A new data pipe. 
5989          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to='LM63 3-site', bundle_to='relax_disp') 
5990          self.interpreter.pipe.switch(pipe_name='LM63 3-site') 
5991   
5992          # Set up the model data. 
5993          self.interpreter.relax_disp.select_model(model='LM63 3-site') 
5994          self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to='LM63 3-site', param='r2eff') 
5995          self.interpreter.spin.isotope('15N') 
5996   
5997          # Alias the spins. 
5998          spin1 = return_spin(":1") 
5999          spin2 = return_spin(":2") 
6000   
6001          # The R20 keys. 
6002          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
6003          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
6004   
6005          # Manually set the parameter values. 
6006          spin1.r2 = {r20_key1: 12.0, r20_key2: 12.0} 
6007          spin1.phi_ex_B = 0.1 
6008          spin1.phi_ex_C = 0.5 
6009          spin1.kB = 1500.0 
6010          spin1.kC = 2500.0 
6011          spin2.r2 = {r20_key1: 15.0, r20_key2: 15.0} 
6012          spin2.phi_ex_B = 0.1 
6013          spin2.phi_ex_C = 0.5 
6014          spin2.kB = 1500.0 
6015          spin2.kC = 2500.0 
6016   
6017          # Low precision optimisation. 
6018          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
6019   
6020          # Monte Carlo simulations. 
6021          self.interpreter.monte_carlo.setup(number=3) 
6022          self.interpreter.monte_carlo.create_data(method='back_calc') 
6023          self.interpreter.monte_carlo.initial_values() 
6024          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-2, grad_tol=None, max_iter=10, constraints=True, scaling=True, verbosity=1) 
6025          self.interpreter.monte_carlo.error_analysis() 
6026   
6027          # Save the results. 
6028          self.interpreter.results.write(file='devnull', compress_type=1, force=True) 
6029   
6030          # The model checks. 
6031          print("\n\nOptimised parameters:\n") 
6032          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
6033          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
6034          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
6035          print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin1.phi_ex_B, spin2.phi_ex_B)) 
6036          print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin1.phi_ex_C, spin2.phi_ex_C)) 
6037          print("%-20s %20.15g %20.15g" % ("kB", spin1.kB, spin2.kB)) 
6038          print("%-20s %20.15g %20.15g" % ("kC", spin1.kC, spin2.kC)) 
6039          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
6040          self.assertAlmostEqual(spin1.r2[r20_key1], 12.0, 2) 
6041          self.assertAlmostEqual(spin1.r2[r20_key2], 12.0, 2) 
6042          self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 
6043          self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 
6044          self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 
6045          self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 
6046          self.assertAlmostEqual(spin1.chi2, 0.0, 3) 
6047          self.assertAlmostEqual(spin2.r2[r20_key1], 15.0, 3) 
6048          self.assertAlmostEqual(spin2.r2[r20_key2], 15.0, 3) 
6049          self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 
6050          self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 
6051          self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 
6052          self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 
6053          self.assertAlmostEqual(spin2.chi2, 0.0, 3) 
6054   
6055   
6056 -    def test_m61_data_to_m61(self): 
6057          """Test the relaxation dispersion 'M61' model curve fitting to fixed time synthetic data.""" 
6058   
6059          # Fixed time variable. 
6060          ds.fixed = True 
6061   
6062          # Execute the script. 
6063          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 
6064   
6065          # The original parameters. 
6066          i0 = [100000.0, 20000.0] 
6067          r1rho_prime = [2.25, 24.0] 
6068          pA = 0.7 
6069          kex = 1000.0 
6070          delta_omega = [1.0, 2.0] 
6071          keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 
6072          phi_ex = [] 
6073          for i in range(2): 
6074              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
6075          rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 
6076   
6077          # Switch to the 'R2eff' model data pipe, then check for each spin. 
6078          self.interpreter.pipe.switch('R2eff - relax_disp') 
6079          spin_index = 0 
6080          for spin, spin_id in spin_loop(return_id=True): 
6081              # Printout. 
6082              print("\nSpin %s." % spin_id) 
6083   
6084              # Check the fitted parameters. 
6085              for i in range(len(keys)): 
6086                  self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 
6087   
6088              # Increment the spin index. 
6089              spin_index += 1 
6090   
6091          # The R20 keys. 
6092          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6093   
6094          # Switch to the 'M61' model data pipe, then check for each spin. 
6095          self.interpreter.pipe.switch('M61 - relax_disp') 
6096          spin_index = 0 
6097          for spin, spin_id in spin_loop(return_id=True): 
6098              # Printout. 
6099              print("\nSpin %s." % spin_id) 
6100   
6101              # Check the fitted parameters. 
6102              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6103              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
6104              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6105   
6106              # Increment the spin index. 
6107              spin_index += 1 
6108   
6109   
6110 -    def test_m61_exp_data_to_m61(self): 
6111          """Test the relaxation dispersion 'M61' model curve fitting to the full exponential synthetic data.""" 
6112   
6113          # Fixed time variable. 
6114          ds.fixed = False 
6115   
6116          # Single spin optimisation. 
6117          ds.single = True 
6118   
6119          # Execute the script. 
6120          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 
6121   
6122          # The original parameters. 
6123          i0 = [100000.0, 20000.0] 
6124          r1rho_prime = [2.25, 24.0] 
6125          pA = 0.7 
6126          kex = 1000.0 
6127          delta_omega = [1.0, 2.0] 
6128          keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 
6129          phi_ex = [] 
6130          for i in range(2): 
6131              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
6132          rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 
6133   
6134          # Switch to the 'R2eff' model data pipe, then check for each spin. 
6135          self.interpreter.pipe.switch('R2eff - relax_disp') 
6136          spin_index = 0 
6137          for spin, spin_id in spin_loop(return_id=True): 
6138              # Printout. 
6139              print("\nSpin %s." % spin_id) 
6140   
6141              # Check the fitted parameters. 
6142              for i in range(len(keys)): 
6143                  self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 
6144   
6145              # Increment the spin index. 
6146              spin_index += 1 
6147   
6148          # The R20 keys. 
6149          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6150   
6151          # Switch to the 'M61' model data pipe, then check for each spin. 
6152          self.interpreter.pipe.switch('M61 - relax_disp') 
6153          spin_index = 0 
6154          for spin, spin_id in spin_loop(return_id=True): 
6155              # Printout. 
6156              print("\nSpin %s." % spin_id) 
6157   
6158              # Check the fitted parameters. 
6159              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6160              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
6161              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6162   
6163              # Increment the spin index. 
6164              spin_index += 1 
6165   
6166   
6167 -    def test_m61b_data_to_m61b(self): 
6168          """Test the relaxation dispersion 'M61 skew' model curve fitting to fixed time synthetic data.""" 
6169   
6170          # Execute the script. 
6171          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61b.py') 
6172   
6173          # The original parameters. 
6174          i0 = [100000.0, 20000.0] 
6175          r1rho_prime = [10.0, 24.0] 
6176          pA = 0.95 
6177          kex = 2000.0 
6178          delta_omega = [1.0, 2.0] 
6179   
6180          # The R20 keys. 
6181          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6182   
6183          # Switch to the 'M61 skew' model data pipe, then check for each spin. 
6184          self.interpreter.pipe.switch("%s - relax_disp" % MODEL_M61B) 
6185          spin_index = 0 
6186          for spin, spin_id in spin_loop(return_id=True): 
6187              # Printout. 
6188              print("\nSpin %s." % spin_id) 
6189   
6190              # Check the fitted parameters. 
6191              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6192              self.assertAlmostEqual(spin.pA, pA, 2) 
6193              self.assertAlmostEqual(spin.dw, dw[spin_index], 2) 
6194              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6195   
6196              # Increment the spin index. 
6197              spin_index += 1 
6198   
6199   
6200 -    def test_model_nesting_and_param(self): 
6201          """Test that all models which can nest, have all their parameters converted.""" 
6202   
6203          # Set the experiment type. 
6204          cdp.exp_type_list = EXP_TYPE_LIST 
6205   
6206          # Get info for all models. 
6207          all_models_info = models_info(models=MODEL_LIST_FULL) 
6208   
6209          # Loop over all models. 
6210          print("Printing the listed of nested models for each model.") 
6211          print("#########################################") 
6212          for model_info in all_models_info: 
6213              print("%s"%model_info.model), 
6214              print("<-"), 
6215              nest_list = model_info.nest_list 
6216              if nest_list == None: 
6217                  nest_list = ["None"] 
6218              print(', '.join(map(str, nest_list))) 
6219   
6220              # Skip if there is no model to nest from. 
6221              if nest_list == ["None"]: 
6222                  continue 
6223   
6224              # Assign params to variable. 
6225              model_params = model_info.params 
6226   
6227              # Now loop over the nested models. 
6228              for nested_model in nest_list: 
6229                  # Get the params for the nested model. 
6230                  nested_model_params = MODEL_PARAMS[nested_model] 
6231   
6232                  # Get the dictionary of parameter conversion. 
6233                  par_dic = nesting_param(model_params=model_params, nested_model_params=nested_model_params) 
6234   
6235                  # Test the number of elements in the dictionary. 
6236                  self.assertEqual(len(par_dic), len(model_params)) 
6237   
6238                  # Loop over dictionary. 
6239                  for param in par_dic: 
6240                          if param != par_dic[param]: 
6241                              print("Model:'%s', Nested model:'%s', Copying '%s' to '%s'." % (model_info.model, nested_model, par_dic[param], param)) 
6242                          self.assertNotEqual(par_dic[param], None) 
6243   
6244   
6245 -    def test_ns_mmq_3site(self): 
6246          """Compare the 'NS MMQ 3-site' dispersion model to synthetic data from cpmg_fit.""" 
6247   
6248          # Execute the script. 
6249          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site.py') 
6250   
6251          # Check the chi-squared value. 
6252          self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3) 
6253   
6254   
6255 -    def test_ns_mmq_3site_linear(self): 
6256          """Compare the 'NS MMQ 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 
6257   
6258          # Execute the script. 
6259          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site_linear.py') 
6260   
6261          # Check the chi-squared value. 
6262          self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3) 
6263   
6264   
6265 -    def test_ns_r1rho_3site(self): 
6266          """Compare the 'NS R1rho 3-site' dispersion model to synthetic data from cpmg_fit.""" 
6267   
6268          # Execute the script. 
6269          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site.py') 
6270   
6271          # Check the chi-squared value. 
6272          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 136.13141468674999, 3) 
6273   
6274   
6275 -    def test_ns_r1rho_3site_linear(self): 
6276          """Compare the 'NS R1rho 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 
6277   
6278          # Execute the script. 
6279          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site_linear.py') 
6280   
6281          # Check the chi-squared value. 
6282          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 0.030959849811015544, 3) 
6283   
6284   
6285 -    def test_repeat_cpmg(self): 
6286          """Test the protocol for repeated dispersion analysis. The class: relax_disp_repeat_cpmg. 
6287   
6288          U{task #7826<https://gna.org/task/index.php?7826>}. Write an python class for the repeated analysis of dispersion data. 
6289          """ 
6290   
6291          # Reset. 
6292          self.interpreter.reset() 
6293   
6294          # Define base path to files. 
6295          base_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1' 
6296   
6297          # Setup dictionary with settings. 
6298          sdic = {} 
6299           
6300          # Spectrometer frqs in list. 
6301          sfrq_1 = 499.86214 
6302          sfrq_2 = 599.8908587 
6303          sfrqs = [sfrq_1, sfrq_2] 
6304           
6305          # Store in dictionary. 
6306          sdic['sfrqs'] = sfrqs 
6307           
6308          # Store unit for frq. 
6309          sdic['sfrq_unit'] = 'MHz' 
6310           
6311          # Store exp_type 
6312          sdic['exp_type'] = 'SQ CPMG' 
6313   
6314          # Store spin isotope 
6315          sdic['isotope'] = '15N' 
6316   
6317          # How intensity was measured. 
6318          sdic['int_method'] = 'height' 
6319   
6320          # Define the time for result directory. 
6321          sdic['time'] = '2014_09' 
6322   
6323          # Initialize frq dics. 
6324          for frq in sfrqs: 
6325              key = DIC_KEY_FORMAT % (frq) 
6326              sdic[key] = {} 
6327           
6328          # Set keys. 
6329          e_1 = DIC_KEY_FORMAT % (sfrq_1) 
6330          e_2 = DIC_KEY_FORMAT % (sfrq_2) 
6331           
6332          # Store time T2. 
6333          sdic[e_1]['time_T2'] = 0.04 
6334          sdic[e_2]['time_T2'] = 0.06 
6335           
6336          # Set ncyc. 
6337          ncyc_1 = array([20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0]) 
6338          ncyc_2 = array([28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 52, 18, 40, 6, 12, 0, 24, 14, 22]) 
6339   
6340          # Calculate the cpmg_frq and store. 
6341          sdic[e_1]['cpmg_frqs'] = ncyc_1 / sdic[e_1]['time_T2'] 
6342          sdic[e_2]['cpmg_frqs'] = ncyc_2 / sdic[e_2]['time_T2'] 
6343           
6344          # Define peak lists. 
6345          peaks_folder_1 = base_path +sep+ 'cpmg_disp_sod1d90a_060518' +sep+ 'cpmg_disp_sod1d90a_060518_normal.fid' +sep+ 'analysis_FT' +sep+ 'ser_files' 
6346          peaks_folder_2 = base_path +sep+ 'cpmg_disp_sod1d90a_060521' +sep+ 'cpmg_disp_sod1d90a_060521_normal.fid' +sep+ 'analysis_FT' +sep+ 'ser_files'  
6347          sdic[e_1]['peaks_folder'] = peaks_folder_1 
6348          sdic[e_2]['peaks_folder'] = peaks_folder_2 
6349           
6350          # Define folder to all rmsd files. 
6351          rmsd_folder_1 = base_path +sep+ 'cpmg_disp_sod1d90a_060518' +sep+ 'cpmg_disp_sod1d90a_060518_normal.fid' +sep+ 'ft2_data' 
6352          rmsd_folder_2 = base_path +sep+ 'cpmg_disp_sod1d90a_060521' +sep+ 'cpmg_disp_sod1d90a_060521_normal.fid' +sep+ 'ft2_data' 
6353          sdic[e_1]['rmsd_folder'] = rmsd_folder_1  
6354          sdic[e_2]['rmsd_folder'] = rmsd_folder_2 
6355   
6356          # Define temporary folder. 
6357          sdic['results_dir'] = self.tmpdir 
6358   
6359          # Setup class with data. 
6360          RDR =  Relax_disp_rep(sdic) 
6361   
6362          # Setup base information. 
6363          RDR.set_base_cpmg(method='FT', glob_ini=128) 
6364   
6365          methods = ['FT', 'MDD'] 
6366          #methods = ['FT'] 
6367   
6368          # Set the intensity. 
6369          #RDR.set_int(methods=methods, list_glob_ini=[128, 126], set_rmsd=False, set_rep=True) 
6370          #RDR.set_int(methods=methods, list_glob_ini=[128, 126], set_rmsd=True, set_rep=False) 
6371   
6372          # Try plot some intensity correlations. 
6373          if True: 
6374              selection = None 
6375   
6376              # Now make a spin selection. 
6377              int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128, 126], selection=selection) 
6378   
6379              # For mdd 
6380              int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6381   
6382              # Plot correlation of intensity 
6383              fig1 = [[int_ft_sel, int_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6384              fig2 = [[int_ft_sel, int_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6385              corr_data = [fig1, fig2] 
6386   
6387              write_stats = True 
6388              RDR.plot_int_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6389   
6390              # Open stat file. 
6391              if write_stats: 
6392                  for i, corr_data_i in enumerate(corr_data): 
6393                      data, methods, glob_inis = corr_data[i] 
6394                      data_x, data_y = data 
6395                      method_x, method_y = methods 
6396                      glob_ini_x, glob_ini_y = glob_inis 
6397                      x = data_x[str(glob_ini_x)]['peak_intensity_arr'] 
6398                      np = len(x) 
6399   
6400                      file_name_ini = 'int_corr_%s_%s_%s_%s_NP_%i' % (method_x, glob_ini_x, method_y, glob_ini_y, np) 
6401   
6402                      if selection == None: 
6403                          file_name = file_name_ini + '_all.txt' 
6404                      else: 
6405                          file_name = file_name_ini + '_sel.txt' 
6406                      path = RDR.results_dir 
6407                      data = extract_data(file=file_name, dir=path) 
6408   
6409                      # Loop over the lines. 
6410                      for i, data_i in enumerate(data): 
6411                          print(i, data_i) 
6412   
6413   
6414          # Try plot some intensity statistics. 
6415          if True: 
6416              # Collect r2eff values. 
6417              selections = [None, ':2,3'] 
6418              for selection in selections: 
6419                  int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128], selection=selection) 
6420                  int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6421   
6422                  # Get R2eff stats. 
6423                  int_stat_dic = RDR.get_int_stat_dic(list_int_dics=[int_ft_sel, int_mdd_sel], list_glob_ini=[128, 126]) 
6424   
6425                  ## Plot R2eff stats 
6426                  write_stats = True 
6427                  RDR.plot_int_stat(int_stat_dic=int_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126], show=False, write_stats=write_stats) 
6428   
6429                  # Open stat file. 
6430                  if write_stats: 
6431                      if selection == None: 
6432                          file_name = 'int_stat_all.txt' 
6433                      else: 
6434                          file_name = 'int_stat_sel.txt' 
6435                      path = RDR.results_dir 
6436                      data = extract_data(file=file_name, dir=path) 
6437   
6438                      # Loop over the lines. 
6439                      for i, data_i in enumerate(data): 
6440                          print(i, data_i) 
6441   
6442   
6443          # Try write some R2eff correlations. 
6444          if True: 
6445              selection = None 
6446              # Collect r2eff values. 
6447              r2eff_ft_all = RDR.col_r2eff(method='FT', list_glob_ini=[128, 126, 6], selection=selection) 
6448   
6449              # For all spins, mdd 
6450              r2eff_mdd_all = RDR.col_r2eff(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6451   
6452              # Plot correlation of intensity 
6453              fig1 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 128]] 
6454              fig2 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 126]] 
6455              corr_data = [fig1, fig2] 
6456   
6457              write_stats = True 
6458              RDR.plot_r2eff_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6459   
6460              # Open stat file. 
6461              if write_stats: 
6462                  for i, corr_data_i in enumerate(corr_data): 
6463                      data, methods, glob_inis = corr_data[i] 
6464                      data_x, data_y = data 
6465                      method_x, method_y = methods 
6466                      glob_ini_x, glob_ini_y = glob_inis 
6467                      x = data_x[str(glob_ini_x)]['r2eff_arr'] 
6468                      np = len(x) 
6469   
6470                      file_name_ini = 'r2eff_corr_%s_%s_%s_%s_NP_%i' % (method_x, glob_ini_x, method_y, glob_ini_y, np) 
6471   
6472                      if selection == None: 
6473                          file_name = file_name_ini + '_all.txt' 
6474                      else: 
6475                          file_name = file_name_ini + '_sel.txt' 
6476                      path = RDR.results_dir 
6477                      data = extract_data(file=file_name, dir=path) 
6478   
6479                      # Loop over the lines. 
6480                      for i, data_i in enumerate(data): 
6481                          print(i, data_i) 
6482   
6483   
6484          # Try plot some R2eff statistics. 
6485          if True: 
6486              # Collect r2eff values. 
6487              selections = [None, ':2,3'] 
6488              for selection in selections: 
6489                  r2eff_ft_sel = RDR.col_r2eff(method='FT', list_glob_ini=[128, 126, 6], selection=selection) 
6490                  r2eff_mdd_sel = RDR.col_r2eff(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6491   
6492                  # Get R2eff stats. 
6493                  r2eff_stat_dic = RDR.get_r2eff_stat_dic(list_r2eff_dics=[r2eff_ft_sel, r2eff_mdd_sel], list_glob_ini=[128, 126]) 
6494   
6495                  ## Plot R2eff stats 
6496                  write_stats = True 
6497                  RDR.plot_r2eff_stat(r2eff_stat_dic=r2eff_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6498   
6499                  # Open stat file. 
6500                  if write_stats: 
6501                      if selection == None: 
6502                          file_name = 'r2eff_stat_all.txt' 
6503                      else: 
6504                          file_name = 'r2eff_stat_sel.txt' 
6505                      path = RDR.results_dir 
6506                      data = extract_data(file=file_name, dir=path) 
6507   
6508                      # Loop over the lines. 
6509                      for i, data_i in enumerate(data): 
6510                          print(i, data_i) 
6511   
6512   
6513          # Do minimisation individual. 
6514          if True: 
6515              methods = ['FT', 'MDD'] 
6516              # Now calculate R2eff. 
6517              RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126]) 
6518   
6519              min_methods = [['FT'], ['MDD']] 
6520              min_list_glob_ini = [[128], list(range(126, 130, 2))[::-1]] 
6521   
6522              #min_methods = [['FT']] 
6523              #min_list_glob_ini = [[128]] 
6524              #selection = ':2,3' 
6525              selection = None 
6526   
6527              for i, methods in enumerate(min_methods): 
6528                  list_glob_ini = min_list_glob_ini[i] 
6529   
6530                  if True: 
6531                      # First get data. 
6532                      if True: 
6533                          # First load all data. 
6534                          RDR.calc_r2eff(methods=methods, list_glob_ini=list_glob_ini) 
6535   
6536                      # Then set R20 
6537                      if True: 
6538                          # Set R20 from min R2eff in preparation for Grid search. 
6539                          RDR.r20_from_min_r2eff(methods=methods, model=MODEL_CR72, model_from=MODEL_R2EFF, analysis='grid_setup_ind', analysis_from='int', list_glob_ini=list_glob_ini, force=True) 
6540   
6541                      # Check and print parameters. 
6542                      if True: 
6543                          # Print for pipe name 
6544                          method = methods[0] 
6545                          glob_ini = list_glob_ini[0] 
6546   
6547                          test_pipe_name = RDR.name_pipe(method=method, model=MODEL_CR72, analysis='grid_setup_ind', glob_ini=glob_ini) 
6548                          RDR.spin_display_params(pipe_name=test_pipe_name) 
6549   
6550                      # Then Grid search. 
6551                      if True: 
6552                          # Do Grid search. 
6553                          RDR.minimise_grid_search(inc=4, verbosity=1, methods=methods, model=MODEL_CR72, analysis='grid_setup_ind', list_glob_ini=list_glob_ini, force=True) 
6554   
6555                  # Then Minimise. 
6556                  if True: 
6557                      # Minimise 
6558                      RDR.opt_max_iterations = int(1e2) 
6559                      RDR.minimise_execute(methods=methods, model=MODEL_CR72, analysis='min_ind', analysis_from='grid_setup_ind', list_glob_ini=list_glob_ini, force=True) 
6560   
6561                  #print asd 
6562   
6563          # Plot statistics. 
6564          # Try plot some minimisation correlations. 
6565          if True: 
6566              selections = [None, ':2,3'] 
6567              for selection in selections: 
6568                  # Collect param values. 
6569                  analysis = 'min_ind' 
6570                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6571                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6572   
6573                  fig1 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6574                  fig2 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6575                  corr_data = [fig1, fig2] 
6576   
6577                  write_stats = True 
6578                  RDR.plot_min_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6579   
6580                  # Open stat file. 
6581                  if write_stats: 
6582                      for i, corr_data_i in enumerate(corr_data): 
6583                          data, methods, glob_inis = corr_data[i] 
6584                          data_x, data_y = data 
6585                          method_x, method_y = methods 
6586                          glob_ini_x, glob_ini_y = glob_inis 
6587   
6588                          file_name_ini = '%s_%s_%s_%s_%s' % (analysis, method_x, glob_ini_x, method_y, glob_ini_y) 
6589   
6590                          if selection == None: 
6591                              file_name = file_name_ini + '_all.txt' 
6592                          else: 
6593                              file_name = file_name_ini + '_sel.txt' 
6594                          path = RDR.results_dir 
6595                          data = extract_data(file=file_name, dir=path) 
6596   
6597                          # Loop over the lines. 
6598                          for i, data_i in enumerate(data): 
6599                              print(i, data_i) 
6600   
6601          # Try plot some minimisation statistics. 
6602          if True: 
6603              # Collect param values. 
6604              #selections = [None, ':2,3'] 
6605              selections = [None, ':2,3'] 
6606              for selection in selections: 
6607                  analysis = 'min_ind' 
6608                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6609                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6610   
6611                  # Get param stats. 
6612                  min_stat_dic = RDR.get_min_stat_dic(list_r2eff_dics=[min_ft_sel, min_mdd_sel], list_glob_ini=[128, 126]) 
6613   
6614                  ## Plot R2eff stats 
6615                  write_stats = True 
6616                  RDR.plot_min_stat(min_stat_dic=min_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6617   
6618                  # Open stat file. 
6619                  if write_stats: 
6620                      if selection == None: 
6621                          file_name = '%s_stat_all.txt' % (analysis) 
6622                      else: 
6623                          file_name = '%s_stat_sel.txt' % (analysis) 
6624                      path = RDR.results_dir 
6625                      data = extract_data(file=file_name, dir=path) 
6626   
6627                      # Loop over the lines. 
6628                      for i, data_i in enumerate(data): 
6629                          print(i, data_i) 
6630   
6631   
6632          # Do minimisation clustered. 
6633          if True: 
6634              methods = ['FT', 'MDD'] 
6635              # Now calculate R2eff. 
6636              RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126]) 
6637   
6638              min_methods = [['FT'], ['MDD']] 
6639              min_list_glob_ini = [[128], list(range(126, 130, 2))[::-1]] 
6640   
6641              #min_methods = [['FT']] 
6642              #min_list_glob_ini = [[128]] 
6643              selection = ':2,3' 
6644   
6645              for i, methods in enumerate(min_methods): 
6646                  list_glob_ini = min_list_glob_ini[i] 
6647   
6648                  if True: 
6649                      # First get data. 
6650                      if True: 
6651                          # First load all data. 
6652                          RDR.calc_r2eff(methods=methods, list_glob_ini=list_glob_ini) 
6653                       
6654                      # Then select spins. 
6655                      if True: 
6656                          # Deselect all spins. 
6657                          RDR.deselect_all(methods=methods, model='setup', model_from=MODEL_R2EFF, analysis='grid_setup', analysis_from='int', list_glob_ini=list_glob_ini, force=True) 
6658                   
6659                          RDR.select_spin(spin_id=selection, methods=methods, model='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6660                   
6661                      # Then preset values. 
6662                      if True: 
6663                          # Set k_AB for Grid search. 
6664                          RDR.value_set(methods=methods, val=1000., param='kex', model=MODEL_CR72, model_from='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6665                          RDR.value_set(methods=methods, val=0.95, param='pA', model=MODEL_CR72, model_from='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6666                   
6667                      # Then set R20 
6668                      if True: 
6669                          # Set R20 from min R2eff in preparation for Grid search. 
6670                          RDR.r20_from_min_r2eff(methods=methods, model=MODEL_CR72, analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6671                   
6672                      # Check and print parameters. 
6673                      if True: 
6674                          # Print for pipe name 
6675                          method = methods[0] 
6676                          glob_ini = list_glob_ini[0] 
6677   
6678                          test_pipe_name = RDR.name_pipe(method=method, model=MODEL_CR72, analysis='grid_setup', glob_ini=glob_ini) 
6679                          RDR.spin_display_params(pipe_name=test_pipe_name) 
6680                       
6681                      # Then Grid search. 
6682                      if True: 
6683                          # Do Grid search. 
6684                          RDR.minimise_grid_search(inc=200, verbosity=1, methods=methods, model=MODEL_CR72, analysis='grid', analysis_from='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6685                   
6686                      # Then cluster spins. 
6687                      if True: 
6688                          RDR.cluster_spins(spin_id=selection, methods=methods, model=MODEL_CR72, analysis='grid', list_glob_ini=list_glob_ini, force=True) 
6689               
6690                  # Then Minimise. 
6691                  if True: 
6692                      # Minimise 
6693                      RDR.opt_max_iterations = int(1e2) 
6694                      RDR.minimise_execute(methods=methods, model=MODEL_CR72, analysis='min', analysis_from='grid', list_glob_ini=list_glob_ini, force=False) 
6695   
6696          # Plot statistics. 
6697          # Try plot some minimisation correlations. 
6698          if True: 
6699              selection = ':2,3' 
6700              # Collect param values. 
6701              analysis = 'min' 
6702              min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6703              min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6704   
6705              fig1 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6706              fig2 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6707              corr_data = [fig1, fig2] 
6708   
6709              write_stats = True 
6710              RDR.plot_min_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6711   
6712              # Open stat file. 
6713              if write_stats: 
6714                  for i, corr_data_i in enumerate(corr_data): 
6715                      data, methods, glob_inis = corr_data[i] 
6716                      data_x, data_y = data 
6717                      method_x, method_y = methods 
6718                      glob_ini_x, glob_ini_y = glob_inis 
6719   
6720                      file_name_ini = '%s_%s_%s_%s_%s' % (analysis, method_x, glob_ini_x, method_y, glob_ini_y) 
6721   
6722                      if selection == None: 
6723                          file_name = file_name_ini + '_all.txt' 
6724                      else: 
6725                          file_name = file_name_ini + '_sel.txt' 
6726                      path = RDR.results_dir 
6727                      data = extract_data(file=file_name, dir=path) 
6728   
6729                      # Loop over the lines. 
6730                      for i, data_i in enumerate(data): 
6731                          print(i, data_i) 
6732   
6733          # Try plot some minimisation statistics. 
6734          if True: 
6735              # Collect param values. 
6736              selections = [':2,3'] 
6737              for selection in selections: 
6738                  analysis = 'min' 
6739                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6740                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6741   
6742                  # Get param stats. 
6743                  min_stat_dic = RDR.get_min_stat_dic(list_r2eff_dics=[min_ft_sel, min_mdd_sel], list_glob_ini=[128, 126]) 
6744   
6745                  ## Plot R2eff stats 
6746                  write_stats = True 
6747                  RDR.plot_min_stat(min_stat_dic=min_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6748   
6749                  # Open stat file. 
6750                  if write_stats: 
6751                      if selection == None: 
6752                          file_name = '%s_stat_all.txt' % (analysis) 
6753                      else: 
6754                          file_name = '%s_stat_sel.txt' % (analysis) 
6755                      path = RDR.results_dir 
6756                      data = extract_data(file=file_name, dir=path) 
6757   
6758                      # Loop over the lines. 
6759                      for i, data_i in enumerate(data): 
6760                          print(i, data_i) 
6761   
6762   
6763   
6764 -    def test_r1rho_kjaergaard_auto(self): 
6765          """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
6766   
6767          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
6768   
6769          This uses the automatic analysis. 
6770   
6771          """ 
6772   
6773          # Cluster residues 
6774          cluster_ids = [ 
6775          ":13@N", 
6776          ":15@N", 
6777          ":16@N", 
6778          ":25@N", 
6779          ":26@N", 
6780          ":28@N", 
6781          ":39@N", 
6782          ":40@N", 
6783          ":41@N", 
6784          ":43@N", 
6785          ":44@N", 
6786          ":45@N", 
6787          ":49@N", 
6788          ":52@N", 
6789          ":53@N"] 
6790   
6791          # Load the data. 
6792          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids) 
6793   
6794          # Test some of the sequence. 
6795          self.assertEqual(len(cdp.mol), 1) 
6796          self.assertEqual(cdp.mol[0].name, None) 
6797          self.assertEqual(len(cdp.mol[0].res), 48) 
6798   
6799          # Test the chemical shift data. 
6800          cs = [122.223, 122.162, 114.250, 125.852, 118.626, 117.449, 119.999, 122.610, 118.602, 118.291, 115.393, 
6801          121.288, 117.448, 116.378, 116.316, 117.263, 122.211, 118.748, 118.103, 119.421, 119.317, 119.386, 117.279, 
6802          122.103, 120.038, 116.698, 111.811, 118.639, 118.285, 121.318, 117.770, 119.948, 119.759, 118.314, 118.160, 
6803          121.442, 118.714, 113.080, 125.706, 119.183, 120.966, 122.361, 126.675, 117.069, 120.875, 109.372, 119.811, 126.048] 
6804   
6805          i = 0 
6806          for spin, spin_id in spin_loop(return_id=True): 
6807              # Check the chemical shift. 
6808              self.assertEqual(spin.chemical_shift, cs[i]) 
6809   
6810              # Increment the index. 
6811              i += 1 
6812   
6813          # Initialize counter 
6814          i = 0 
6815          j = 0 
6816          # Count instances of select/deselect 
6817          for curspin, mol_name, res_num, res_name, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
6818              if curspin.select == True: 
6819                  i += 1 
6820              if curspin.select == False: 
6821                  j += 1 
6822   
6823          # Test number of selected/deselected spins. 
6824          self.assertEqual(i, len(cluster_ids)) 
6825          self.assertEqual(j, 48-len(cluster_ids)) 
6826   
6827          # Check the initial setup. 
6828          self.assertEqual(cdp.mol[0].res[7].num, 13) 
6829          self.assertEqual(cdp.mol[0].res[7].spin[0].kex, ds.guess[':13@N'][6]) 
6830          self.assertEqual(cdp.mol[0].res[7].spin[0].ri_data['R1'], ds.ref[':13@N'][2]) 
6831   
6832          self.assertEqual(cdp.mol[0].res[9].num, 15) 
6833          self.assertEqual(cdp.mol[0].res[9].spin[0].kex, ds.guess[':15@N'][6]) 
6834          self.assertEqual(cdp.mol[0].res[9].spin[0].ri_data['R1'], ds.ref[':15@N'][2]) 
6835   
6836          self.assertEqual(cdp.mol[0].res[10].num, 16) 
6837          self.assertEqual(cdp.mol[0].res[10].spin[0].kex, ds.guess[':16@N'][6]) 
6838          self.assert_(hasattr(cdp.mol[0].res[10].spin[0], 'ri_data')) 
6839   
6840          self.assertEqual(cdp.mol[0].res[16].num, 25) 
6841          self.assertEqual(cdp.mol[0].res[16].spin[0].kex, ds.guess[':25@N'][6]) 
6842          self.assert_(hasattr(cdp.mol[0].res[16].spin[0], 'ri_data')) 
6843   
6844          self.assertEqual(cdp.mol[0].res[17].num, 26) 
6845          self.assertEqual(cdp.mol[0].res[17].spin[0].kex, ds.guess[':26@N'][6]) 
6846          self.assert_(hasattr(cdp.mol[0].res[17].spin[0], 'ri_data')) 
6847   
6848          self.assertEqual(cdp.mol[0].res[19].num, 28) 
6849          self.assertEqual(cdp.mol[0].res[19].spin[0].kex, ds.guess[':28@N'][6]) 
6850          self.assert_(hasattr(cdp.mol[0].res[19].spin[0], 'ri_data')) 
6851   
6852          self.assertEqual(cdp.mol[0].res[29].num, 39) 
6853          self.assertEqual(cdp.mol[0].res[29].spin[0].kex, ds.guess[':39@N'][6]) 
6854          self.assert_(hasattr(cdp.mol[0].res[29].spin[0], 'ri_data')) 
6855   
6856          self.assertEqual(cdp.mol[0].res[30].num, 40) 
6857          self.assertEqual(cdp.mol[0].res[30].spin[0].kex, ds.guess[':40@N'][6]) 
6858          self.assert_(hasattr(cdp.mol[0].res[30].spin[0], 'ri_data')) 
6859   
6860          self.assertEqual(cdp.mol[0].res[31].num, 41) 
6861          self.assertEqual(cdp.mol[0].res[31].spin[0].kex, ds.guess[':41@N'][6]) 
6862          self.assert_(hasattr(cdp.mol[0].res[31].spin[0], 'ri_data')) 
6863   
6864          self.assertEqual(cdp.mol[0].res[33].num, 43) 
6865          self.assertEqual(cdp.mol[0].res[33].spin[0].kex, ds.guess[':43@N'][6]) 
6866          self.assert_(hasattr(cdp.mol[0].res[33].spin[0], 'ri_data')) 
6867   
6868          self.assertEqual(cdp.mol[0].res[34].num, 44) 
6869          self.assertEqual(cdp.mol[0].res[34].spin[0].kex, ds.guess[':44@N'][6]) 
6870          self.assert_(hasattr(cdp.mol[0].res[34].spin[0], 'ri_data')) 
6871   
6872          self.assertEqual(cdp.mol[0].res[35].num, 45) 
6873          self.assertEqual(cdp.mol[0].res[35].spin[0].kex, ds.guess[':45@N'][6]) 
6874          self.assert_(hasattr(cdp.mol[0].res[35].spin[0], 'ri_data')) 
6875   
6876          self.assertEqual(cdp.mol[0].res[38].num, 49) 
6877          self.assertEqual(cdp.mol[0].res[38].spin[0].kex, ds.guess[':49@N'][6]) 
6878          self.assert_(hasattr(cdp.mol[0].res[38].spin[0], 'ri_data')) 
6879   
6880          self.assertEqual(cdp.mol[0].res[41].num, 52) 
6881          self.assertEqual(cdp.mol[0].res[41].spin[0].kex, ds.guess[':52@N'][6]) 
6882          self.assert_(hasattr(cdp.mol[0].res[41].spin[0], 'ri_data')) 
6883   
6884          self.assertEqual(cdp.mol[0].res[42].num, 53) 
6885          self.assertEqual(cdp.mol[0].res[42].spin[0].kex, ds.guess[':53@N'][6]) 
6886          self.assert_(hasattr(cdp.mol[0].res[42].spin[0], 'ri_data')) 
6887   
6888          # The dispersion models. 
6889          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
6890   
6891          # The grid search size (the number of increments per dimension). 
6892          GRID_INC = 4 
6893   
6894          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
6895          MC_NUM = 3 
6896   
6897          # Model selection technique. 
6898          MODSEL = 'AIC' 
6899   
6900          # Execute the auto-analysis (fast). 
6901          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
6902          OPT_FUNC_TOL = 1e-1 
6903          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
6904          OPT_MAX_ITERATIONS = 1000 
6905          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
6906   
6907          result_dir_name = ds.tmpdir 
6908   
6909          # Make all spins free 
6910          for curspin in cluster_ids: 
6911              self.interpreter.relax_disp.cluster('free spins', curspin) 
6912              # Shut them down 
6913              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
6914   
6915          # Select only a subset of spins for global fitting 
6916          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
6917          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
6918   
6919          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
6920          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
6921   
6922          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
6923          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
6924   
6925          # Run the analysis. 
6926          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
6927   
6928          # Check the kex value of residue 52 
6929          #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ds.ref[':52@N'][6]) 
6930   
6931          # Print results for each model. 
6932          print("\n\n################") 
6933          print("Printing results") 
6934          print("################\n") 
6935          for model in MODELS: 
6936              # Skip R2eff model. 
6937              if model == MODEL_R2EFF: 
6938                  continue 
6939   
6940              # Switch to pipe. 
6941              self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
6942              print("\nModel: %s" % (model)) 
6943   
6944              # Loop over the spins. 
6945              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
6946                  # Generate spin string. 
6947                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
6948   
6949                  # Loop over the parameters. 
6950                  print("Optimised parameters for spin: %s" % (spin_string)) 
6951                  for param in cur_spin.params + ['chi2']: 
6952                      # Get the value. 
6953                      if param in ['r1', 'r2']: 
6954                          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
6955                              # Generate the R20 key. 
6956                              r20_key = generate_r20_key(exp_type=exp_type, frq=frq) 
6957   
6958                              # Get the value. 
6959                              value = getattr(cur_spin, param)[r20_key] 
6960   
6961                              # Print value. 
6962                              print("%-10s %-6s %-6s %3.3f" % ("Parameter:", param, "Value:", value)) 
6963   
6964                      # For all other parameters. 
6965                      else: 
6966                          # Get the value. 
6967                          value = getattr(cur_spin, param) 
6968   
6969                          # Print value. 
6970                          print("%-10s %-6s %-6s %3.3f" % ("Parameter:", param, "Value:", value)) 
6971   
6972          # Print the final pipe. 
6973          self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % ('final')) 
6974          print("\nFinal pipe") 
6975   
6976   
6977 -    def test_r1rho_kjaergaard_auto_check_graphs(self): 
6978          """Check of plot_disp_curves() function, after optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'R2eff' model. 
6979   
6980          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
6981   
6982          This uses the automatic analysis. 
6983   
6984          """ 
6985   
6986          # Cluster residues 
6987          cluster_ids = [ 
6988          ":52@N"] 
6989   
6990          # Load the data. 
6991          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids) 
6992   
6993          # The dispersion models. 
6994          MODELS = [MODEL_R2EFF] 
6995   
6996          # The grid search size (the number of increments per dimension). 
6997          GRID_INC = 4 
6998   
6999          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7000          MC_NUM = 3 
7001   
7002          # Model selection technique. 
7003          MODSEL = 'AIC' 
7004   
7005          # Execute the auto-analysis (fast). 
7006          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7007          OPT_FUNC_TOL = 1e-1 
7008          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7009          OPT_MAX_ITERATIONS = 1000 
7010          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7011   
7012          result_dir_name = ds.tmpdir 
7013   
7014          # Make all spins free 
7015          for curspin in cluster_ids: 
7016              self.interpreter.relax_disp.cluster('free spins', curspin) 
7017              # Shut them down 
7018              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
7019   
7020          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
7021   
7022          # Run the analysis. 
7023          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
7024   
7025          # Check the graphs produced. 
7026          graph_comb = [ 
7027          [Y_AXIS_R2_EFF, X_AXIS_DISP, INTERPOLATE_DISP], 
7028          [Y_AXIS_R2_EFF, X_AXIS_THETA, INTERPOLATE_DISP], 
7029          [Y_AXIS_R2_R1RHO, X_AXIS_W_EFF, INTERPOLATE_DISP], 
7030          [Y_AXIS_R2_EFF, X_AXIS_THETA, INTERPOLATE_OFFSET] 
7031          ] 
7032   
7033          # Define expected folder names. 
7034          result_folders = MODELS 
7035   
7036          # Assign spin_id. 
7037          spin_id = ':52@N' 
7038   
7039          # Loop over result folders. 
7040          for result_folder in result_folders: 
7041              # Skip the model R2eff, which does not produce graphs. 
7042              if result_folder == MODEL_R2EFF: 
7043                  continue 
7044   
7045              # Loop over graphs. 
7046              for y_axis, x_axis, interpolate in graph_comb: 
7047                  # Determine file name: 
7048                  file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
7049   
7050                  # Make the file name. 
7051                  file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
7052   
7053                  # Get the file path. 
7054                  file_path = get_file_path(file_name, result_dir_name+sep+result_folder) 
7055   
7056                  print("Testing file access to graph: %s"%file_path) 
7057                  self.assert_(access(file_path, F_OK)) 
7058   
7059          # Start testing all possible combinations of graphs. 
7060          y_axis_types = [Y_AXIS_R2_EFF, Y_AXIS_R2_R1RHO] 
7061          x_axis_types = [X_AXIS_DISP, X_AXIS_THETA, X_AXIS_W_EFF] 
7062          interpolate_types = [INTERPOLATE_DISP, INTERPOLATE_OFFSET] 
7063   
7064          result_dir_name = ds.tmpdir 
7065   
7066          # Loop through all possible combinations of y_axis, x_axis and interpolation. 
7067          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep+'check_graphs' 
7068   
7069          for result_folder in result_folders: 
7070              # Skip the model R2eff, which does not produce graphs. 
7071              if result_folder == MODEL_R2EFF: 
7072                  continue 
7073   
7074              for y_axis in y_axis_types: 
7075                  for x_axis in x_axis_types: 
7076                      for interpolate in interpolate_types: 
7077                          # Determine file name: 
7078                          file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
7079   
7080                          # Make the file name. 
7081                          file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
7082   
7083                          # Write the curves. 
7084                          dir = result_dir_name+sep+result_folder 
7085                          print("Plotting combination of %s, %s, %s"%(y_axis, x_axis, interpolate)) 
7086                          self.interpreter.relax_disp.plot_disp_curves(dir=dir, y_axis=y_axis, x_axis=x_axis, interpolate=interpolate, force=True) 
7087   
7088                          # Get the file path. 
7089                          file_path = get_file_path(file_name, dir) 
7090   
7091                          # Test the plot file exists. 
7092                          print("Testing file access to graph: %s"%file_path) 
7093                          self.assert_(access(file_path, F_OK)) 
7094   
7095                          # Now open, and compare content, line by line. 
7096                          file_prod = open(file_path) 
7097                          lines_prod = file_prod.readlines() 
7098                          file_prod.close() 
7099   
7100                          # Define file to compare against. 
7101                          dir_comp = data_path+sep+result_folder 
7102                          file_path_comp = get_file_path(file_name, dir_comp) 
7103                          file_comp = open(file_path_comp) 
7104                          lines_comp = file_comp.readlines() 
7105                          file_comp.close() 
7106   
7107                          # Assert number of lines is equal. 
7108                          self.assertEqual(len(lines_prod), len(lines_comp)) 
7109                          for j in range(len(lines_prod)): 
7110                              # Make the string test 
7111                              first_char = lines_prod[j][0] 
7112                              if first_char in ["@", "&"]: 
7113                                  self.assertEqual(lines_prod[j], lines_comp[j]) 
7114                              else: 
7115                                  # Split string in x, y, error. 
7116                                  # The error would change per run. 
7117                                  x_prod, y_prod, y_prod_err = lines_prod[j].split() 
7118                                  x_comp, y_comp, y_comp_err = lines_comp[j].split() 
7119                                  self.assertAlmostEqual(float(x_prod), float(x_comp)) 
7120                                  self.assertAlmostEqual(float(y_prod), float(y_comp)) 
7121   
7122   
7123 -    def test_r1rho_kjaergaard_missing_r1(self): 
7124          """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
7125   
7126          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
7127   
7128          This uses the automatic analysis, with missing loading R1. 
7129   
7130          """ 
7131   
7132          # Cluster residues 
7133          cluster_ids = [ 
7134          ":13@N", 
7135          ":15@N", 
7136          ":16@N", 
7137          ":25@N", 
7138          ":26@N", 
7139          ":28@N", 
7140          ":39@N", 
7141          ":40@N", 
7142          ":41@N", 
7143          ":43@N", 
7144          ":44@N", 
7145          ":45@N", 
7146          ":49@N", 
7147          ":52@N", 
7148          ":53@N"] 
7149   
7150          # Load the data. 
7151          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
7152   
7153          # The dispersion models. 
7154          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
7155   
7156          # The grid search size (the number of increments per dimension). 
7157          GRID_INC = None 
7158   
7159          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7160          MC_NUM = 3 
7161   
7162          # Model selection technique. 
7163          MODSEL = 'AIC' 
7164   
7165          # Execute the auto-analysis (fast). 
7166          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7167          OPT_FUNC_TOL = 1e-25 
7168          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7169          OPT_MAX_ITERATIONS = 10000000 
7170          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7171   
7172          result_dir_name = ds.tmpdir 
7173   
7174          # Make all spins free 
7175          for curspin in cluster_ids: 
7176              self.interpreter.relax_disp.cluster('free spins', curspin) 
7177              # Shut them down 
7178              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
7179   
7180          # Select only a subset of spins for global fitting 
7181          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
7182          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
7183   
7184          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
7185          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
7186   
7187          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
7188          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
7189   
7190          # Point to directory with R2eff values, with 2000 MC simulations. 
7191          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000" 
7192   
7193          r1_fit = True 
7194   
7195          # Run the analysis. 
7196          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, pre_run_dir=prev_data_path, r1_fit=r1_fit) 
7197   
7198          # Verify the data. 
7199          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='MC2000') 
7200   
7201   
7202 -    def test_r2eff_read(self): 
7203          """Test the operation of the relax_disp.r2eff_read user function.""" 
7204   
7205          # The path to the data files. 
7206          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'800_MHz' 
7207   
7208          # Read the sequence data. 
7209          self.interpreter.sequence.read(file='66.667.in', dir=data_path, res_num_col=1) 
7210   
7211          # The ID. 
7212          id = 'test' 
7213   
7214          # Set up the metadata. 
7215          self.interpreter.spectrometer.frequency(id=id, frq=800e6) 
7216          self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
7217   
7218          # Try reading the file. 
7219          self.interpreter.relax_disp.r2eff_read(id=id, file='66.667.in', dir=data_path, disp_frq=66.667, res_num_col=1, data_col=2, error_col=3) 
7220   
7221          # Check the global data. 
7222          data = [ 
7223              ['cpmg_frqs', {'test': 66.667}], 
7224              ['cpmg_frqs_list', [66.667]], 
7225              ['dispersion_points', 1], 
7226              ['exp_type', {'test': 'SQ CPMG'}], 
7227              ['exp_type_list', ['SQ CPMG']], 
7228              ['spectrometer_frq', {'test': 800000000.0}], 
7229              ['spectrometer_frq_count', 1], 
7230              ['spectrometer_frq_list', [800000000.0]], 
7231              ['spectrum_ids', ['test']] 
7232          ] 
7233          for name, value in data: 
7234              # Does it exist? 
7235              self.assert_(hasattr(cdp, name)) 
7236   
7237              # Check the object. 
7238              obj = getattr(cdp, name) 
7239              self.assertEqual(obj, value) 
7240   
7241          # Check the spin data. 
7242          data = [ 
7243              [1,       2.3035747e+04, 8.5467725e+01], 
7244              [2,       9.9629762e+04, 2.8322033e+02], 
7245              [3,       9.5663137e+04, 2.8632929e+02], 
7246              [4,       1.7089893e+05, 3.1089428e+02], 
7247              [5,       4.7323876e+04, 1.0084269e+02], 
7248              [6,       2.0199122e+04, 1.0135220e+02], 
7249              [7,       1.6655488e+05, 3.1609061e+02], 
7250              [8,       9.0061074e+04, 1.9176585e+02], 
7251              [10,      8.4726204e+04, 2.8898155e+02], 
7252              [11,      1.5050233e+05, 4.3138029e+02], 
7253              [12,      9.2998531e+04, 3.0440191e+02], 
7254              [13,      1.6343507e+05, 3.3144097e+02], 
7255              [14,      1.0137301e+05, 3.7314642e+02], 
7256              [15,      8.3407837e+04, 1.6546473e+02], 
7257              [16,      1.3819126e+05, 3.3388517e+02], 
7258              [17,      1.1010490e+05, 3.5639222e+02], 
7259              [18,      9.4324035e+04, 3.2343585e+02], 
7260              [19,      1.1135179e+05, 3.0706671e+02], 
7261              [20,      7.6339410e+04, 1.7377460e+02], 
7262              [21,      6.2008453e+04, 1.7327150e+02], 
7263              [22,      1.0590404e+05, 2.4814635e+02], 
7264              [23,      1.0630198e+05, 2.3601100e+02], 
7265              [24,      7.2996320e+04, 1.4952465e+02], 
7266              [25,      9.5486742e+04, 2.7080766e+02], 
7267              [26,      5.8067989e+04, 1.6820462e+02], 
7268              [27,     -1.7168510e+04, 2.2519560e+02], 
7269              [28,      1.6891473e+05, 2.3497525e+02], 
7270              [29,      9.4038555e+04, 2.0357593e+02], 
7271              [30,      2.1386951e+04, 2.2153532e+02], 
7272              [31,      9.3982899e+04, 2.0937056e+02], 
7273              [32,      8.6097484e+04, 2.3868467e+02], 
7274              [33,      1.0194337e+05, 2.7370704e+02], 
7275              [34,      8.5683111e+04, 2.0838076e+02], 
7276              [35,      8.6985768e+04, 2.0889310e+02], 
7277              [36,      8.6011237e+04, 1.7498390e+02], 
7278              [37,      1.0984097e+05, 2.7622998e+02], 
7279              [38,      8.7017879e+04, 2.6547994e+02], 
7280              [39,      9.1682649e+04, 5.2777676e+02], 
7281              [40,      7.6370440e+04, 1.9873214e+02], 
7282              [41,      9.1393531e+04, 2.4483824e+02], 
7283              [42,      1.1017111e+05, 2.8020699e+02], 
7284              [43,      9.4552366e+04, 3.4394150e+02], 
7285              [44,      1.2858281e+05, 6.8449252e+02], 
7286              [45,      7.4583525e+04, 1.9544210e+02], 
7287              [46,      9.2087490e+04, 2.0491066e+02], 
7288              [47,      9.7507255e+04, 2.5162839e+02], 
7289              [48,      1.0033842e+05, 2.7566430e+02], 
7290              [49,      1.3048305e+05, 2.6797466e+02], 
7291              [50,      1.0546796e+05, 1.9304384e+02], 
7292              [51,      9.3099697e+04, 2.0773311e+02], 
7293              [52,      4.6863758e+04, 1.3169068e+02], 
7294              [53,      6.1055806e+04, 1.5448477e+02], 
7295              [55,      6.8629994e+04, 1.6868673e+02], 
7296              [56,      1.1005552e+05, 2.1940465e+02], 
7297              [57,      1.0572760e+05, 1.9768486e+02], 
7298              [58,      1.1176950e+05, 3.0009610e+02], 
7299              [59,      9.8758603e+04, 3.3803895e+02], 
7300              [60,      9.9517201e+04, 3.5137994e+02], 
7301              [61,      5.4357946e+04, 2.5896579e+02], 
7302              [62,      1.0899978e+05, 2.8720371e+02], 
7303              [63,      8.4549759e+04, 4.1401837e+02], 
7304              [64,      5.5014550e+04, 2.1135781e+02], 
7305              [65,      8.0569666e+04, 2.3249709e+02], 
7306              [66,      1.2936610e+05, 3.5218725e+02], 
7307              [67,      3.6438010e+04, 8.7924003e+01], 
7308              [70,      3.8763157e+04, 1.3325040e+02], 
7309              [71,      8.5711411e+04, 2.9316183e+02], 
7310              [72,      3.3211541e+04, 1.2182123e+02], 
7311              [73,      3.2070576e+04, 1.2305430e+02] 
7312          ] 
7313          for res_num, value, error in data: 
7314              # Get the spin. 
7315              spin = return_spin(spin_id=":%s"%res_num) 
7316   
7317              # Check the values. 
7318              self.assertEqual(spin.r2eff['sq_cpmg_800.00000000_0.000_66.667'], value) 
7319              self.assertEqual(spin.r2eff_err['sq_cpmg_800.00000000_0.000_66.667'], error) 
7320   
7321   
7322 -    def test_r2eff_read_spin(self): 
7323          """Test the operation of the relax_disp.r2eff_read_spin user function.""" 
7324   
7325          # The path to the data files. 
7326          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 
7327   
7328          # Generate the sequence. 
7329          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 
7330          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 
7331          self.interpreter.spin.isotope('1H', spin_id='@H') 
7332          self.interpreter.spin.isotope('15N', spin_id='@N') 
7333   
7334          # Build the experiment IDs. 
7335          H_disp_points = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 
7336          N_disp_points = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
7337          ids = [] 
7338          for value in H_disp_points: 
7339              ids.append('1H_CPMG_%s' % value) 
7340          for value in N_disp_points: 
7341              ids.append('15N_CPMG_%s' % value) 
7342          print("\n\nThe experiment IDs are %s." % ids) 
7343   
7344          # Set up the metadata for the experiments. 
7345          for id in ids: 
7346              self.interpreter.spectrometer.frequency(id=id, frq=500e6) 
7347              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
7348          for value in H_disp_points: 
7349              self.interpreter.relax_disp.cpmg_setup(spectrum_id='1H_CPMG_%s' % value, cpmg_frq=value) 
7350          for value in N_disp_points: 
7351              self.interpreter.relax_disp.cpmg_setup(spectrum_id='15N_CPMG_%s' % value, cpmg_frq=value) 
7352   
7353          # Loop over the experiments. 
7354          for id, file, spin_id in [['1H_CPMG', 'hs_500.res', ':9@H'], ['15N_CPMG', 'ns_500.res', ':9@N']]: 
7355              # Try reading the file. 
7356              self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 
7357   
7358          # Check the global data. 
7359          data = [ 
7360              ['cpmg_frqs', {'1H_CPMG_667.0': 667.0, '1H_CPMG_1067.0': 1067.0, '15N_CPMG_350.0': 350.0, '1H_CPMG_933.0': 933.0, '15N_CPMG_50.0': 50.0, '15N_CPMG_100.0': 100.0, '1H_CPMG_400.0': 400.0, '1H_CPMG_533.0': 533.0, '1H_CPMG_800.0': 800.0, '15N_CPMG_900.0': 900.0, '15N_CPMG_150.0': 150.0, '15N_CPMG_800.0': 800.0, '1H_CPMG_267.0': 267.0, '1H_CPMG_2667.0': 2667.0, '15N_CPMG_300.0': 300.0, '1H_CPMG_133.0': 133.0, '15N_CPMG_700.0': 700.0, '1H_CPMG_67.0': 67.0, '15N_CPMG_400.0': 400.0, '15N_CPMG_250.0': 250.0, '1H_CPMG_2133.0': 2133.0, '1H_CPMG_1600.0': 1600.0, '15N_CPMG_200.0': 200.0, '15N_CPMG_1000.0': 1000.0, '15N_CPMG_500.0': 500.0, '15N_CPMG_600.0': 600.0}], 
7361              ['cpmg_frqs_list', [50.0, 67.0, 100.0, 133.0, 150.0, 200.0, 250.0, 267.0, 300.0, 350.0, 400.0, 500.0, 533.0, 600.0, 667.0, 700.0, 800.0, 900.0, 933.0, 1000.0, 1067.0, 1600.0, 2133.0, 2667.0]], 
7362              ['dispersion_points', 24], 
7363              ['exp_type', {'1H_CPMG_667.0': 'SQ CPMG', '1H_CPMG_1067.0': 'SQ CPMG', '15N_CPMG_350.0': 'SQ CPMG', '1H_CPMG_933.0': 'SQ CPMG', '15N_CPMG_50.0': 'SQ CPMG', '15N_CPMG_100.0': 'SQ CPMG', '1H_CPMG_400.0': 'SQ CPMG', '1H_CPMG_533.0': 'SQ CPMG', '1H_CPMG_800.0': 'SQ CPMG', '15N_CPMG_900.0': 'SQ CPMG', '15N_CPMG_150.0': 'SQ CPMG', '15N_CPMG_800.0': 'SQ CPMG', '1H_CPMG_267.0': 'SQ CPMG', '1H_CPMG_2667.0': 'SQ CPMG', '15N_CPMG_300.0': 'SQ CPMG', '1H_CPMG_133.0': 'SQ CPMG', '15N_CPMG_700.0': 'SQ CPMG', '1H_CPMG_67.0': 'SQ CPMG', '15N_CPMG_400.0': 'SQ CPMG', '15N_CPMG_250.0': 'SQ CPMG', '1H_CPMG_2133.0': 'SQ CPMG', '1H_CPMG_1600.0': 'SQ CPMG', '15N_CPMG_200.0': 'SQ CPMG', '15N_CPMG_1000.0': 'SQ CPMG', '15N_CPMG_500.0': 'SQ CPMG', '15N_CPMG_600.0': 'SQ CPMG'}], 
7364              ['exp_type_list', ['SQ CPMG']], 
7365              ['spectrometer_frq', {'1H_CPMG_667.0': 500000000.0, '1H_CPMG_1067.0': 500000000.0, '15N_CPMG_350.0': 500000000.0, '1H_CPMG_933.0': 500000000.0, '15N_CPMG_50.0': 500000000.0, '15N_CPMG_100.0': 500000000.0, '1H_CPMG_400.0': 500000000.0, '1H_CPMG_533.0': 500000000.0, '1H_CPMG_800.0': 500000000.0, '15N_CPMG_900.0': 500000000.0, '15N_CPMG_150.0': 500000000.0, '15N_CPMG_800.0': 500000000.0, '1H_CPMG_267.0': 500000000.0, '1H_CPMG_2667.0': 500000000.0, '15N_CPMG_300.0': 500000000.0, '1H_CPMG_133.0': 500000000.0, '15N_CPMG_700.0': 500000000.0, '1H_CPMG_67.0': 500000000.0, '15N_CPMG_400.0': 500000000.0, '15N_CPMG_250.0': 500000000.0, '1H_CPMG_2133.0': 500000000.0, '1H_CPMG_1600.0': 500000000.0, '15N_CPMG_200.0': 500000000.0, '15N_CPMG_1000.0': 500000000.0, '15N_CPMG_500.0': 500000000.0, '15N_CPMG_600.0': 500000000.0}], 
7366              ['spectrometer_frq_count', 1], 
7367              ['spectrometer_frq_list', [500000000.0]], 
7368              ['spectrum_ids', ['1H_CPMG_67.0', '1H_CPMG_133.0', '1H_CPMG_267.0', '1H_CPMG_400.0', '1H_CPMG_533.0', '1H_CPMG_667.0', '1H_CPMG_800.0', '1H_CPMG_933.0', '1H_CPMG_1067.0', '1H_CPMG_1600.0', '1H_CPMG_2133.0', '1H_CPMG_2667.0', '15N_CPMG_50.0', '15N_CPMG_100.0', '15N_CPMG_150.0', '15N_CPMG_200.0', '15N_CPMG_250.0', '15N_CPMG_300.0', '15N_CPMG_350.0', '15N_CPMG_400.0', '15N_CPMG_500.0', '15N_CPMG_600.0', '15N_CPMG_700.0', '15N_CPMG_800.0', '15N_CPMG_900.0', '15N_CPMG_1000.0']] 
7369          ] 
7370          for name, value in data: 
7371              # Does it exist? 
7372              self.assert_(hasattr(cdp, name)) 
7373   
7374              # Check the object. 
7375              obj = getattr(cdp, name) 
7376              if not isinstance(data, dict): 
7377                  self.assertEqual(obj, value) 
7378   
7379              # Check the global dictionary data. 
7380              else: 
7381                  for id in ids: 
7382                      self.assertEqual(obj[id], value[id]) 
7383   
7384          # Check the spin data. 
7385          h_data = [ 
7386              [  67.0,  21.47924,   0.42958], 
7387              [ 133.0,  16.73898,   0.33478], 
7388              [ 267.0,   9.97357,   0.19947], 
7389              [ 400.0,   8.23877,   0.24737], 
7390              [ 533.0,   7.59290,   0.24263], 
7391              [ 667.0,   7.45843,   0.24165], 
7392              [ 800.0,   7.11222,   0.23915], 
7393              [ 933.0,   7.40880,   0.24129], 
7394              [1067.0,   6.55191,   0.16629], 
7395              [1600.0,   6.72177,   0.23637], 
7396              [2133.0,   7.09629,   0.23904], 
7397              [2667.0,   7.14675,   0.23940] 
7398          ] 
7399          for disp_point, value, error in h_data: 
7400              id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 
7401              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
7402              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
7403          n_data = [ 
7404              [  50.0,  27.15767,   0.54315], 
7405              [ 100.0,  26.55781,   0.53116], 
7406              [ 150.0,  24.73462,   0.49469], 
7407              [ 200.0,  20.98617,   0.41972], 
7408              [ 250.0,  17.82442,   0.35649], 
7409              [ 300.0,  15.55352,   0.31107], 
7410              [ 350.0,  13.78958,   0.27579], 
7411              [ 400.0,  12.48334,   0.24967], 
7412              [ 500.0,  11.55724,   0.23114], 
7413              [ 600.0,  10.53874,   0.21077], 
7414              [ 700.0,  10.07395,   0.20148], 
7415              [ 800.0,   9.62952,   0.19259], 
7416              [ 900.0,   9.49994,   0.19000], 
7417              [1000.0,   8.71350,   0.17427] 
7418          ] 
7419          for disp_point, value, error in n_data: 
7420              id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 
7421              self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff[id], value) 
7422              self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff_err[id], error) 
7423   
7424   
7425 -    def test_r2eff_fit_fixed_time(self): 
7426          """Test the relaxation dispersion 'R2eff' model for fixed time data in the auto-analysis.""" 
7427   
7428          # Execute the script. 
7429          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r2eff_calc.py') 
7430   
7431   
7432 -    def test_read_r2eff(self): 
7433          """Test the reading of a file containing r2eff values.""" 
7434   
7435          # Create the sequence data, and name the spins. 
7436          self.interpreter.residue.create(1, 'Gly') 
7437          self.interpreter.residue.create(2, 'Gly') 
7438          self.interpreter.residue.create(3, 'Gly') 
7439   
7440          # Read the file. 
7441          self.interpreter.relax_data.read(ri_id='R2eff.600', ri_type='R2eff', frq=600*1e6, file='r2eff.out', dir=status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r2eff', res_num_col=1, res_name_col=2, data_col=3, error_col=4) 
7442   
7443          # Test the data. 
7444          self.assertEqual(cdp.mol[0].res[0].spin[0].ri_data['R2eff.600'], 15.000) 
7445          self.assertEqual(cdp.mol[0].res[1].spin[0].ri_data['R2eff.600'], 4.2003) 
7446          self.assertEqual(cdp.mol[0].res[2].spin[0].ri_data['R2eff.600'], 7.2385) 
7447   
7448   
7449 -    def test_r20_from_min_r2eff_cpmg(self): 
7450          """Test speeding up grid search. Support requst sr #3151 U{https://gna.org/support/index.php?3151}. 
7451   
7452          User function to set the R20 parameters in the default grid search using the minimum R2eff value. 
7453   
7454          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7455          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7456   
7457          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7458          Data is for experiment at 25 degree Celcius. 
7459          """ 
7460   
7461          # Base data setup. 
7462          pipe_name = 'base pipe' 
7463          pipe_type = 'relax_disp' 
7464          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7465          select_spin_index = list(range(0, 1)) 
7466          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7467   
7468          # Generate r20 key. 
7469          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7470          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7471   
7472          ## Now prepare for MODEL calculation. 
7473          MODEL = "CR72" 
7474   
7475          # Change pipe. 
7476          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
7477          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7478          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7479   
7480          # Then select model. 
7481          self.interpreter.relax_disp.select_model(model=MODEL) 
7482   
7483          # Set the R20 parameters in the default grid search using the minimum R2eff value. 
7484          self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
7485   
7486          # Test result, for normal run. 
7487          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7488              # Get the spin_params. 
7489              spin_params = spin.params 
7490   
7491              # Defined fixed values for testing. 
7492              if spin_id == ":10@N": 
7493                  self.assertEqual(spin.r2[r20_key_600], 20.282732526087106) 
7494                  self.assertEqual(spin.r2[r20_key_500], 18.475299724356649) 
7495   
7496              # Print out. 
7497              print("r2_600=%2.2f r2_500=%2.2f spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin_id, resi, resn)) 
7498   
7499              # Testing the r2 values for the different fields are not the same. 
7500              self.assert_(spin.r2[r20_key_600] != spin.r2[r20_key_500]) 
7501   
7502              # Test values are larger than 0. 
7503              self.assert_(spin.r2[r20_key_600] > 0.0) 
7504              self.assert_(spin.r2[r20_key_500] > 0.0) 
7505   
7506              # Loop over the experiment settings. 
7507              r2eff_600 = [] 
7508              r2eff_500 = [] 
7509              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
7510                  # Create the data key. 
7511                  data_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
7512   
7513                  # Extract the r2 eff data. 
7514                  r2eff = spin.r2eff[data_key] 
7515                  if frq == 599.8908617*1E6: 
7516                      r2eff_600.append(r2eff) 
7517                  elif frq == 499.862139*1E6: 
7518                      r2eff_500.append(r2eff) 
7519   
7520              # Sort values. 
7521              r2eff_600.sort() 
7522              r2eff_500.sort() 
7523   
7524              # Test values again. 
7525              print("For r20 600MHz min r2eff=%3.3f."%(min(r2eff_600))) 
7526              print(r2eff_600) 
7527              self.assertEqual(spin.r2[r20_key_600], min(r2eff_600)) 
7528              print("") 
7529   
7530              print("For r20 500MHz min r2eff=%3.3f."%(min(r2eff_500))) 
7531              print(r2eff_500) 
7532              self.assertEqual(spin.r2[r20_key_500], min(r2eff_500)) 
7533              print("") 
7534   
7535          print("###########################################") 
7536          print("Trying GRID SEARCH for minimum R2eff values") 
7537   
7538          ### Test just the Grid search. 
7539          GRID_INC = 5 
7540   
7541          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7542   
7543          ### Then test the value.set function. 
7544          # Change pipe. 
7545          pipe_name_MODEL = "%s_%s_2"%(pipe_name, MODEL) 
7546          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7547          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7548   
7549          # Then select model. 
7550          self.interpreter.relax_disp.select_model(model=MODEL) 
7551   
7552          # Then set the standard parameter values. 
7553          for param in spin_params: 
7554              print("Setting standard parameter for param: %s"%param) 
7555              self.interpreter.value.set(param=param, index=None) 
7556   
7557          # Test result, for normal run. 
7558          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7559              # Print out. 
7560              print("r2_600=%2.2f r2_500=%2.2f pA=%2.2f, dw=%2.2f, kex=%2.2f, spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin.pA, spin.dw, spin.kex, spin_id, resi, resn)) 
7561   
7562              # Testing the r2 values. 
7563              self.assertEqual(spin.r2[r20_key_600], 10.00) 
7564              self.assertEqual(spin.r2[r20_key_500], 10.00) 
7565              self.assertEqual(spin.pA, 0.9) 
7566              self.assertEqual(spin.dw, 1.0) 
7567              self.assertEqual(spin.kex, 1000.0) 
7568   
7569          print("###########################################") 
7570          print("Trying GRID SEARCH for standard R2eff values") 
7571   
7572          ### Test just the Grid search. 
7573          GRID_INC = 5 
7574   
7575          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7576   
7577          ### Run auto_analysis. 
7578          # The grid search size (the number of increments per dimension). 
7579          GRID_INC = 5 
7580   
7581          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7582          MC_NUM = 3 
7583   
7584          # Model selection technique. 
7585          MODSEL = 'AIC' 
7586   
7587          # Execute the auto-analysis (fast). 
7588          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7589          OPT_FUNC_TOL = 1e-1 
7590          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7591          OPT_MAX_ITERATIONS = 1000 
7592          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7593   
7594          # Run the analysis. 
7595          relax_disp.Relax_disp(pipe_name=pipe_name_r2eff, results_dir=ds.tmpdir, models=[MODEL], grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, set_grid_r20=True) 
7596   
7597   
7598 -    def test_show_apod_extract(self): 
7599          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod.""" 
7600   
7601          # The path to the data files. 
7602          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7603   
7604          # Define file name. 
7605          file_name = '128_0_FT.ft2' 
7606   
7607          # Call function. 
7608          get_output = show_apod_extract(file_name=file_name, dir=data_path) 
7609   
7610          # Define how output should look like. 
7611          # The output from showApod differs slightly according to NMRPipe version. But 'Noise Std Dev' is the same. 
7612          # Dont test lines which can differ. 
7613          show_apod_ver = [ 
7614              'REMARK Effect of Processing on Peak Parameters and Noise for %s'%(data_path+sep+file_name), 
7615              'REMARK Automated Noise Std Dev in Processed Data: 8583.41', 
7616              'REMARK Noise Std Dev Before Processing H1 and N15: 60.6558', 
7617              '', 
7618              'VARS   AXIS LABEL  TSIZE FSIZE LW_ADJ LW_FINAL HI_FACTOR VOL_FACTOR SIGMA_FACTOR', 
7619              'FORMAT %s   %-8s   %4d   %4d   %7.4f  %7.4f    %.4e      %.4e       %.4e'] 
7620              #'', 
7621              #'       X    H1       800  2048 0.8107 3.7310   4.9903e-03 9.8043e-04 5.2684e-02', 
7622              #'       Y    N15      128   256 0.7303 3.0331   3.1260e-02 7.8434e-03 1.3413e-01'] 
7623   
7624          for i, line in enumerate(show_apod_ver): 
7625              line_ver = get_output[i] 
7626   
7627              print(line) 
7628              if line[:50] == 'REMARK Noise Std Dev Before Processing H1 and N15:': 
7629                  continue 
7630              # Make the string test 
7631              self.assertEqual(line, line_ver) 
7632   
7633   
7634 -    def test_show_apod_rmsd(self): 
7635          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod.""" 
7636   
7637          # The path to the data files. 
7638          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7639   
7640          # Define file name. 
7641          file_name = '128_0_FT.ft2' 
7642   
7643          # Call function. 
7644          rmsd = show_apod_rmsd(file_name=file_name, dir=data_path) 
7645   
7646          # Assert. 
7647          self.assertEqual(rmsd, 8583.41) 
7648   
7649   
7650 -    def test_show_apod_rmsd_dir_to_files(self): 
7651          """Test searching for all NMRPipe spectrum files in dir, call showApod, and write to files.""" 
7652   
7653          # The path to the data files. 
7654          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7655   
7656          # Call function, and get all file names. 
7657          wfile_paths = show_apod_rmsd_dir_to_files(file_ext='.ft2', dir=data_path, outdir=self.tmpdir) 
7658   
7659          # Loop over file_paths. 
7660          for wfile_path in wfile_paths: 
7661              # Open the file. 
7662              get_data = extract_data(file=wfile_path) 
7663   
7664              # Extract line 0, column 0. 
7665              test = float(get_data[0][0]) 
7666   
7667              # Assert. 
7668              self.assertEqual(test, 8583.41) 
7669   
7670   
7671 -    def test_show_apod_rmsd_to_file(self): 
7672          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod, and write to file.""" 
7673   
7674          # The path to the data files. 
7675          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7676   
7677          # Define file name. 
7678          file_name = '128_0_FT.ft2' 
7679   
7680          # Call function, and get file name. 
7681          wfile_path = show_apod_rmsd_to_file(file_name=file_name, dir=data_path, outdir=self.tmpdir) 
7682   
7683          # Open the file. 
7684          get_data = extract_data(file=wfile_path) 
7685   
7686          # Extract line 0, column 0. 
7687          test = float(get_data[0][0]) 
7688   
7689          # Assert. 
7690          self.assertEqual(test, 8583.41) 
7691   
7692   
7693 -    def test_sod1wt_t25_bug_21954_order_error_analysis(self): 
7694          """Error analysis of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
7695   
7696          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7697          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7698   
7699          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7700          Data is for experiment at 25 degree Celcius. 
7701   
7702          bug #21954 U{https://gna.org/bugs/index.php?21954}: Order of spectrum.error_analysis is important. 
7703          """ 
7704   
7705          # Base data setup. 
7706          pipe_name = 'base pipe' 
7707          pipe_type = 'relax_disp' 
7708          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7709          select_spin_index = list(range(0, 1)) 
7710          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7711   
7712          # Define replicated 
7713          repl_A = ['Z_A1', 'Z_A15'] 
7714          repl_B = ['Z_B1', 'Z_B18'] 
7715   
7716          # Loop over spectrum ID, and sort them 
7717          spectrum_ids_A = [] 
7718          spectrum_ids_B = [] 
7719          for spectrum_id in cdp.spectrum_ids: 
7720              if "A" in spectrum_id: 
7721                  spectrum_ids_A.append(spectrum_id) 
7722              elif "B" in spectrum_id: 
7723                  spectrum_ids_B.append(spectrum_id) 
7724   
7725          # To clean up old error analysis, delete attributes 
7726          delattr(cdp, "var_I") 
7727          delattr(cdp, "sigma_I") 
7728   
7729          # Perform error analysis 
7730          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 
7731          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 
7732   
7733          # Loop over spins, save errors to list 
7734          Errors_A_B = [] 
7735          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7736              A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 
7737              B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 
7738              Errors_A_B.append([A_err, B_err]) 
7739   
7740          # To clean up old error analysis, delete attributes 
7741          delattr(cdp, "var_I") 
7742          delattr(cdp, "sigma_I") 
7743   
7744          # Perform error analysis. Order is important 
7745          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 
7746          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 
7747   
7748          # Loop over spins, save errors to list 
7749          Errors_B_A = [] 
7750          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7751              A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 
7752              B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 
7753              Errors_B_A.append([A_err, B_err]) 
7754   
7755          # Make test for order of error 
7756          for i in range(len(Errors_A_B)): 
7757              Error_A_B = Errors_A_B[i] 
7758              Error_B_A = Errors_B_A[i] 
7759              self.assertAlmostEqual(Error_A_B[0], Error_B_A[0], 4) 
7760              self.assertAlmostEqual(Error_A_B[1], Error_B_A[1], 4) 
7761   
7762          # Make further tests for fixed values 
7763          std_A = math.sqrt((cdp.var_I[repl_A[0]] + cdp.var_I[repl_A[1]])/2) 
7764          std_A_fix = 2785.7263335738567 
7765   
7766          for id_A in spectrum_ids_A: 
7767              self.assertEqual(cdp.sigma_I[id_A], std_A) 
7768              self.assertAlmostEqual(cdp.sigma_I[id_A], std_A_fix, 7) 
7769   
7770          std_B = math.sqrt((cdp.var_I[repl_B[0]] + cdp.var_I[repl_B[1]])/2) 
7771          std_B_fix = 4967.3772030667988 
7772   
7773          for id_B in spectrum_ids_B: 
7774              self.assertEqual(cdp.sigma_I[id_B], std_B) 
7775              self.assertAlmostEqual(cdp.sigma_I[id_B], std_B_fix, 7) 
7776   
7777   
7778 -    def test_sod1wt_t25_to_cr72(self): 
7779          """Optimisation of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
7780   
7781          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7782          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7783   
7784          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7785          Data is for experiment at 25 degree Celcius. 
7786          """ 
7787   
7788          # Base data setup. 
7789          pipe_name = 'base pipe' 
7790          pipe_type = 'relax_disp' 
7791          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7792          select_spin_index = list(range(0, 2)) 
7793          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7794   
7795          # Generate r20 key. 
7796          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7797          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7798   
7799          ## Now prepare for MODEL calculation. 
7800          MODEL = "CR72" 
7801   
7802          # Change pipe. 
7803          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
7804          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7805          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7806   
7807          # Then select model. 
7808          self.interpreter.relax_disp.select_model(model=MODEL) 
7809   
7810          # GRID inc of 7 was found to be appropriate not to find pA = 0.5. 
7811          GRID_INC = 7 
7812   
7813          # Store grid and minimisations results. 
7814          grid_results = [] 
7815          mini_results = [] 
7816          clust_results = [] 
7817   
7818          # Set the R20 parameters in the default grid search using the minimum R2eff value. 
7819          self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
7820   
7821          # Deselect insignificant spins. 
7822          self.interpreter.relax_disp.insignificance(level=1.0) 
7823   
7824          # Perform Grid Search. 
7825          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7826   
7827          # Store result. 
7828          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7829              # Store grid results. 
7830              grid_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7831   
7832          ## Now do minimisation. 
7833          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7834          set_func_tol = 1e-9 
7835          set_max_iter = 100000 
7836          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
7837   
7838          # Store result. 
7839          pA_values = [] 
7840          kex_values = [] 
7841          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7842              # Store minimisation results. 
7843              mini_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7844   
7845              # Store pA values. 
7846              pA_values.append(spin.pA) 
7847   
7848              # Store kex values. 
7849              kex_values.append(spin.kex) 
7850   
7851          print("\n# Now print before and after minimisation.\n") 
7852   
7853          # Print results. 
7854          for i in range(len(grid_results)): 
7855              # Get values. 
7856              g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
7857              m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
7858   
7859              print("GRID r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
7860              print("MIN  r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
7861   
7862          ## Prepare for clustering 
7863          # Change pipe. 
7864          pipe_name_MODEL_CLUSTER = "%s_%s_Cluster"%(pipe_name, MODEL) 
7865          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL_CLUSTER) 
7866          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL_CLUSTER) 
7867   
7868          # Then select model. 
7869          self.interpreter.relax_disp.select_model(model=MODEL) 
7870   
7871          # Define cluster id. 
7872          cluster_id = 'clust' 
7873   
7874          # Loop over spins to cluster them. 
7875          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7876              self.interpreter.relax_disp.cluster(cluster_id, spin_id) 
7877   
7878          # Copy over values. 
7879          self.interpreter.relax_disp.parameter_copy(pipe_from=pipe_name_MODEL, pipe_to=pipe_name_MODEL_CLUSTER) 
7880   
7881          # Test the median values is correct 
7882          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7883              print(pA_values) 
7884              # The the median pA value returned. 
7885              self.assertEqual(median(pA_values), spin.pA) 
7886   
7887              # The the median kex value returned. 
7888              self.assertEqual(median(kex_values), spin.kex) 
7889   
7890          ## Now do minimisation. 
7891          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
7892   
7893          # Store result. 
7894          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7895              # Store clust results. 
7896              clust_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7897   
7898              # Store the outcome of the clustering minimisation. 
7899              clust_pA = spin.pA 
7900              clust_kex = spin.kex 
7901   
7902          print("\n# Now testing.\n") 
7903   
7904          # Define results 
7905          test_res = {} 
7906          test_res[':10@N'] = {} 
7907          test_res[':10@N']['r2600'] = 18.429755324773360 
7908          test_res[':10@N']['r2500'] = 16.981349161968630 
7909          test_res[':10@N']['dw'] = 2.700755859433969 
7910          test_res[':10@N']['pA'] = 0.971531659288657 
7911          test_res[':10@N']['kex'] = 3831.766337047963134 
7912          test_res[':11@N'] = {} 
7913          test_res[':11@N']['r2600'] = 18.193409421115213 
7914          test_res[':11@N']['r2500'] = 17.308838135567765 
7915          test_res[':11@N']['dw'] = 2.706650302761793 
7916          test_res[':11@N']['pA'] = 0.971531659288657 
7917          test_res[':11@N']['kex'] = 3831.766337047963134 
7918   
7919          # Then make tests. 
7920          for i in range(len(grid_results)): 
7921              # Get values. 
7922              g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
7923              m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
7924              c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn = clust_results[i] 
7925   
7926              print("%s GRID   r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
7927              print("%s MIN    r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
7928              print("%s Clust  r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn)) 
7929   
7930              # Make tests. 
7931              self.assertEqual(clust_pA, c_pA) 
7932              self.assertEqual(clust_kex, c_kex) 
7933   
7934              # Test values. 
7935              if c_spin_id in test_res: 
7936                  self.assertAlmostEqual(c_r2_600, test_res[c_spin_id]['r2600'], 4) 
7937                  self.assertAlmostEqual(c_r2_500, test_res[c_spin_id]['r2500'], 4) 
7938                  self.assertAlmostEqual(c_dw, test_res[c_spin_id]['dw'], 3) 
7939                  self.assertAlmostEqual(c_pA, test_res[c_spin_id]['pA'], 5) 
7940                  self.assertAlmostEqual(c_kex, test_res[c_spin_id]['kex'], 1) 
7941   
7942          # Save disp graph to temp. 
7943          #self.interpreter.relax_disp.plot_disp_curves(dir="~"+sep+"test", num_points=1000, extend=500.0, force=True). 
7944   
7945   
7946 -    def test_sod1wt_t25_to_sherekhan_input(self): 
7947          """Conversion of SOD1-WT CPMG R2eff values into input files for sherekhan. 
7948   
7949          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7950          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7951   
7952          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7953          Data is for experiment at 25 degree Celcius. 
7954          """ 
7955   
7956          # Base data setup. 
7957          pipe_name = 'base pipe' 
7958          pipe_type = 'relax_disp' 
7959          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7960          select_spin_index = list(range(0, 2)) 
7961          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7962   
7963          # Generate r20 key. 
7964          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7965          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7966   
7967          # Cluster everything, to analyse together. 
7968          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-1000") 
7969   
7970          # Write input 
7971          self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=ds.tmpdir) 
7972   
7973          # Check the r2eff set files. 
7974          print("\nChecking the R2eff input set files.") 
7975          files = [[ds.tmpdir + sep + 'cluster1', 'sherekhan_frq1.in'], [ ds.tmpdir + sep + 'cluster1', 'sherekhan_frq2.in']] 
7976   
7977          # First check file exists 
7978          for dir, file in files: 
7979              print(dir+sep+file) 
7980              self.assert_(access(dir+sep+file, F_OK)) 
7981   
7982          # Define how files should look like 
7983          data_set_600 = [ 
7984               "60.8272464287\n", 
7985               "0.06\n", 
7986               "# nu_cpmg (Hz)       R2eff (rad/s)        Error               \n", 
7987               "# G10\n", 
7988               "              33.333       26.53556078711      0.5236104771163\n", 
7989               "              66.667       25.29735243318        0.48766574122\n", 
7990               "                 100       25.09470361403      0.4820438864671\n", 
7991               "             133.333       25.15603274331      0.4837377286085\n", 
7992               "             166.667       24.27213341753      0.4599457904395\n", 
7993               "                 200       24.00364120328      0.4529773198905\n", 
7994               "             266.667       24.03511395168      0.4537880662536\n", 
7995               "                 300       23.04761040024      0.4291039120557\n", 
7996               "             333.333       22.95530300787      0.4268745963972\n", 
7997               "                 400       23.06158810662      0.4294426293624\n", 
7998               "             466.667       22.26799054092      0.4106809618644\n", 
7999               "             533.333       21.99851418823      0.4045232104735\n", 
8000               "             666.667       21.19651570955      0.3868136173831\n", 
8001               "             833.333       20.30938498379      0.3682604887899\n", 
8002               "                1000       20.28273252609       0.367719392568\n", 
8003               "# D11\n", 
8004               "              33.333       24.76520269878      0.5026475808706\n", 
8005               "              66.667        24.8773107448      0.5058752916906\n", 
8006               "                 100       24.90357815239      0.5066348551479\n", 
8007               "             133.333        23.7782506151      0.4751950583865\n", 
8008               "             166.667       23.68548762076      0.4727017128631\n", 
8009               "                 200       23.58629651618      0.4700517377679\n", 
8010               "             266.667       23.47734671187      0.4671601744044\n", 
8011               "                 300       24.08647493772      0.4835855560598\n", 
8012               "             333.333       22.98314371029      0.4542918950801\n", 
8013               "                 400       22.80339361568      0.4497107885587\n", 
8014               "             466.667       22.91634335366      0.4525833037874\n", 
8015               "             533.333       22.59774140046      0.4445334311324\n", 
8016               "             666.667        20.9177750759      0.4046955726046\n", 
8017               "             833.333       20.71792550566      0.4002363835007\n", 
8018               "                1000       19.54080006349      0.3751112751853\n", 
8019          ] 
8020   
8021          # Check data_set_600 
8022          file = open(files[0][0]+sep+files[0][1]) 
8023          lines = file.readlines() 
8024          file.close() 
8025          self.assertEqual(len(data_set_600), len(lines)) 
8026          for i in range(len(data_set_600)): 
8027              # Make the string test 
8028              self.assertEqual(data_set_600[i], lines[i]) 
8029   
8030          # Define how files should look like 
8031          data_set_500 = [ 
8032               "50.6846152368\n", 
8033               "0.04\n", 
8034               "# nu_cpmg (Hz)       R2eff (rad/s)        Error               \n", 
8035               "# G10\n", 
8036               "                  50       22.28084307393      0.2944966344183\n", 
8037               "                 100       21.93494977761      0.2910362768307\n", 
8038               "                 150       21.09850032232       0.282892238351\n", 
8039               "                 200       20.86493960397      0.2806737853646\n", 
8040               "                 250       20.75287269752      0.2796178205016\n", 
8041               "                 300       20.25597152406      0.2750013546989\n", 
8042               "                 350       19.92172163467      0.2719555756504\n", 
8043               "                 400       19.97712052922       0.272457105051\n", 
8044               "                 450       19.46807010415      0.2678972122793\n", 
8045               "                 500       19.76875460947      0.2705774849203\n", 
8046               "                 550       19.39161367402      0.2672216964327\n", 
8047               "                 600       19.03949517697      0.2641417899694\n", 
8048               "                 650       19.12218812132      0.2648605059901\n", 
8049               "                 700       19.01037461457      0.2638893584683\n", 
8050               "                 800       18.83395162904      0.2623674321143\n", 
8051               "                 900       18.47529972436      0.2593123604687\n", 
8052               "                1000        18.5252023121      0.2597343394038\n", 
8053               "# D11\n", 
8054               "                  50       22.15403890237      0.3285588379827\n", 
8055               "                 100       21.80946781746      0.3247185598713\n", 
8056               "                 150       21.77715415505       0.324361526682\n", 
8057               "                 200       21.41647464235      0.3204122024881\n", 
8058               "                 250       21.17099940822      0.3177616325958\n", 
8059               "                 300       21.03740030577      0.3163316496664\n", 
8060               "                 350       20.95393648281      0.3154427665172\n", 
8061               "                 400       20.93311399332       0.315221543436\n", 
8062               "                 450       20.18219905222      0.3073848655291\n", 
8063               "                 500       19.93599065085      0.3048744697057\n", 
8064               "                 550       19.68475725452      0.3023424499113\n", 
8065               "                 600       19.33575433934      0.2988741928798\n", 
8066               "                 650       19.53915692194      0.3008886196853\n", 
8067               "                 700        19.2018754351      0.2975587767134\n", 
8068               "                 800       18.82360965368      0.2938866923878\n", 
8069               "                 900       18.71861761238      0.2928790380131\n", 
8070               "                1000       17.95878049287      0.2857341721151\n", 
8071          ] 
8072   
8073          # Check data_set_500 
8074          file = open(files[1][0]+sep+files[1][1]) 
8075          lines = file.readlines() 
8076          file.close() 
8077          self.assertEqual(len(data_set_500), len(lines)) 
8078          for i in range(len(data_set_500)): 
8079              # Make the string test 
8080              self.assertEqual(data_set_500[i], lines[i]) 
8081   
8082          # Test local dir tests. This will be turned off in system test. 
8083          turn_on_local_dir_test = False 
8084   
8085          if turn_on_local_dir_test: 
8086              ## Now check to local folder with None argument. 
8087              # Write input 
8088              self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None) 
8089   
8090              # Check the r2eff set files. 
8091              print("\nChecking the R2eff input set files.") 
8092              files = [[path.join(getcwd(), 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), 'cluster1'), 'sherekhan_frq2.in']] 
8093   
8094              # First check file exists 
8095              for dir, file in files: 
8096                  print(dir+sep+file) 
8097                  self.assert_(access(dir+sep+file, F_OK)) 
8098   
8099              ## Now check to local folder with dir argument. 
8100              # Write input 
8101              set_dir = "Test_ShereKhan" 
8102              self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=set_dir) 
8103   
8104              # Check the r2eff set files. 
8105              print("\nChecking the R2eff input set files.") 
8106              files = [[path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq2.in']] 
8107   
8108              # First check file exists 
8109              for dir, file in files: 
8110                  print(dir+sep+file) 
8111                  self.assert_(access(dir+sep+file, F_OK)) 
8112   
8113   
8114 -    def test_sprangers_data_to_mmq_cr72(self, model=None): 
8115          """Test the 'MMQ CR72' model fitting against Remco Sprangers' ClpP data. 
8116   
8117          This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102.  This is MMQ CPMG data with a fixed relaxation time period. 
8118          """ 
8119   
8120          # Reset. 
8121          self.interpreter.reset() 
8122   
8123          # Create the data pipe and load the base data. 
8124          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 
8125          self.interpreter.state.load(data_path+sep+'r2eff_values') 
8126   
8127          # The model data pipe. 
8128          model = 'MMQ CR72' 
8129          pipe_name = "%s - relax_disp" % model 
8130          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
8131          self.interpreter.pipe.switch(pipe_name=pipe_name) 
8132   
8133          # Set the model. 
8134          self.interpreter.relax_disp.select_model(model=model) 
8135   
8136          # Cluster everything. 
8137          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 
8138   
8139          # Copy the data. 
8140          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
8141   
8142          # Alias the spins. 
8143          spin135S = cdp.mol[0].res[0].spin[0] 
8144          spin135F = cdp.mol[0].res[0].spin[1] 
8145          spin137S = cdp.mol[0].res[1].spin[0] 
8146          spin137F = cdp.mol[0].res[1].spin[1] 
8147   
8148          # The R20 keys. 
8149          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
8150          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8151   
8152          # Set the cluster specific parameters (only for the first spin). 
8153          spin135S.pA = 0.836591763632 
8154          spin135S.kex = 241.806525261 
8155   
8156          # Set the initial parameter values. 
8157          spin135S.r2 = {r20_key1: 28.2493431552, r20_key2: 31.7517334715} 
8158          spin135S.dw = 0.583003118785 
8159          spin135S.dwH = 0.0361441944301 
8160   
8161          spin135F.r2 = {r20_key1: 42.7201839991, r20_key2: 57.3178617389} 
8162          spin135F.dw = 0.805849745104 
8163          spin135F.dwH = 0.0215791945715 
8164   
8165          spin137S.r2 = {r20_key1: 26.0134115256, r20_key2: 30.575806934} 
8166          spin137S.dw = 0.688107568372 
8167          spin137S.dwH = 0.0344463604043 
8168   
8169          spin137F.r2 = {r20_key1: 46.6969397337, r20_key2: 58.602384101} 
8170          spin137F.dw = 0.94978299907 
8171          spin137F.dwH = 1.4818877939e-07 
8172   
8173          # Low precision optimisation. 
8174          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-10, max_iter=1000) 
8175   
8176          # Printout. 
8177          print("\n\nOptimised parameters:\n") 
8178          print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 
8179          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 
8180          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 
8181          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 
8182          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 
8183          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 
8184          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 
8185          print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 
8186          print("\n        # Set the cluster specific parameters (only for the first spin).") 
8187          print("        spin135S.pA = %s" % spin135S.pA) 
8188          print("        spin135S.kex = %s" % spin135S.kex) 
8189          print("\n        # Set the initial parameter values.") 
8190          print("        spin135S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135S.r2[r20_key1], spin135S.r2[r20_key2])) 
8191          print("        spin135S.dw = %s" % spin135S.dw) 
8192          print("        spin135S.dwH = %s" % spin135S.dwH) 
8193          print("\n        spin135F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135F.r2[r20_key1], spin135F.r2[r20_key2])) 
8194          print("        spin135F.dw = %s" % spin135F.dw) 
8195          print("        spin135F.dwH = %s" % spin135F.dwH) 
8196          print("\n        spin137S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137S.r2[r20_key1], spin137S.r2[r20_key2])) 
8197          print("        spin137S.dw = %s" % spin137S.dw) 
8198          print("        spin137S.dwH = %s" % spin137S.dwH) 
8199          print("\n        spin137F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137F.r2[r20_key1], spin137F.r2[r20_key2])) 
8200          print("        spin137F.dw = %s" % spin137F.dw) 
8201          print("        spin137F.dwH = %s" % spin137F.dwH) 
8202   
8203          # Checks for residue :135S. 
8204          self.assertAlmostEqual(spin135S.r2[r20_key1], 28.2493445347425, 4) 
8205          self.assertAlmostEqual(spin135S.r2[r20_key2], 31.7517352342937, 4) 
8206          self.assertAlmostEqual(spin135S.pA, 0.836591714049569, 4) 
8207          self.assertAlmostEqual(spin135S.dw, 0.583003004605869, 4) 
8208          self.assertAlmostEqual(spin135S.dwH, 0.0361441894065963, 4) 
8209          self.assertAlmostEqual(spin135S.kex/100, 241.806464344233/100, 4) 
8210          self.assertAlmostEqual(spin135S.chi2, 12.4224060116473, 4) 
8211   
8212          # Checks for residue :135F. 
8213          self.assertAlmostEqual(spin135F.r2[r20_key1], 42.7201844426839, 4) 
8214          self.assertAlmostEqual(spin135F.r2[r20_key2], 57.3178718548898, 4) 
8215          self.assertAlmostEqual(spin135F.pA, 0.836591714049569, 4) 
8216          self.assertAlmostEqual(spin135F.dw, 0.805849748711916, 4) 
8217          self.assertAlmostEqual(spin135F.dwH, 0.0215791669142752, 4) 
8218          self.assertAlmostEqual(spin135F.kex/100, 241.806464344233/100, 4) 
8219          self.assertAlmostEqual(spin135F.chi2, 12.4224060116473, 4) 
8220   
8221          # Checks for residue :137S. 
8222          self.assertAlmostEqual(spin137S.r2[r20_key1], 26.013412509919, 4) 
8223          self.assertAlmostEqual(spin137S.r2[r20_key2], 30.5758092335097, 4) 
8224          self.assertAlmostEqual(spin137S.pA, 0.836591714049569, 4) 
8225          self.assertAlmostEqual(spin137S.dw, 0.688107406812537, 4) 
8226          self.assertAlmostEqual(spin137S.dwH, 0.034446357344577, 4) 
8227          self.assertAlmostEqual(spin137S.kex/100, 241.806464344233/100, 4) 
8228          self.assertAlmostEqual(spin137S.chi2, 12.4224060116473, 4) 
8229   
8230          # Checks for residue :137F. 
8231          self.assertAlmostEqual(spin137F.r2[r20_key1], 46.696935090697, 4) 
8232          self.assertAlmostEqual(spin137F.r2[r20_key2], 58.6023842513446, 4) 
8233          self.assertAlmostEqual(spin137F.pA, 0.836591714049569, 4) 
8234          self.assertAlmostEqual(spin137F.dw, 0.94978325541294, 4) 
8235          self.assertAlmostEqual(spin137F.dwH, 1.5189362257653e-07, 4) 
8236          self.assertAlmostEqual(spin137F.kex/100, 241.806464344233/100, 4) 
8237          self.assertAlmostEqual(spin137F.chi2, 12.4224060116473, 4) 
8238   
8239   
8240 -    def test_sprangers_data_to_ns_mmq_2site(self, model=None): 
8241          """Test the 'NS MMQ 2-site' model fitting against Remco Sprangers' ClpP data. 
8242   
8243          This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102.  This is MQ CPMG data with a fixed relaxation time period. 
8244          """ 
8245   
8246          # Reset. 
8247          self.interpreter.reset() 
8248   
8249          # Create the data pipe and load the base data. 
8250          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 
8251          self.interpreter.state.load(data_path+sep+'r2eff_values') 
8252   
8253          # The model data pipe. 
8254          model = 'NS MMQ 2-site' 
8255          pipe_name = "%s - relax_disp" % model 
8256          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
8257          self.interpreter.pipe.switch(pipe_name=pipe_name) 
8258   
8259          # Set the model. 
8260          self.interpreter.relax_disp.select_model(model=model) 
8261   
8262          # Cluster everything. 
8263          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 
8264   
8265          # Copy the data. 
8266          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
8267   
8268          # Alias the spins. 
8269          spin135S = cdp.mol[0].res[0].spin[0] 
8270          spin135F = cdp.mol[0].res[0].spin[1] 
8271          spin137S = cdp.mol[0].res[1].spin[0] 
8272          spin137F = cdp.mol[0].res[1].spin[1] 
8273   
8274          # The R20 keys. 
8275          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8276          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8277   
8278          # Set the cluster specific parameters (only for the first spin). 
8279          spin135S.pA = 0.847378444499757 
8280          spin135S.kex = 264.055604934724329 
8281   
8282          # Set the initial parameter values. 
8283          spin135S.r2 = {r20_key1: 30.315119723745390, r20_key2: 37.411874745645299} 
8284          spin135S.dw = 0.585574008745351 
8285          spin135S.dwH = 0.000000000000002 
8286   
8287          spin135F.r2 = {r20_key1: 41.440843383778287, r20_key2: 56.989726795397893} 
8288          spin135F.dw = 0.856699277665748 
8289          spin135F.dwH = 0.000000000582587 
8290   
8291          spin137S.r2 = {r20_key1: 23.051695938570266, r20_key2: 28.352806483953824} 
8292          spin137S.dw = 0.772904450844973 
8293          spin137S.dwH = 0.183351478512970 
8294   
8295          spin137F.r2 = {r20_key1: 44.702032074210429, r20_key2: 56.453146052685319} 
8296          spin137F.dw = 0.984568590342831 
8297          spin137F.dwH = 0.000000001993458 
8298   
8299          # Low precision optimisation. 
8300          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-5, grad_tol=None, max_iter=100, constraints=True, scaling=True, verbosity=1) 
8301   
8302          # Printout. 
8303          print("\n\nOptimised parameters:\n") 
8304          print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 
8305          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 
8306          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 
8307          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 
8308          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 
8309          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 
8310          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 
8311          print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 
8312   
8313          # FIXME: Remove this temporary return and properly check the results. 
8314          return 
8315   
8316          # Checks for residue :135S. 
8317          self.assertAlmostEqual(spin135S.r2[r20_key1], 30.3151197237454, 4) 
8318          self.assertAlmostEqual(spin135S.r2[r20_key2], 37.4118747456453, 4) 
8319          self.assertAlmostEqual(spin135S.pA, 0.847378444499757, 4) 
8320          self.assertAlmostEqual(spin135S.dw, 0.585574008745351, 4) 
8321          self.assertAlmostEqual(spin135S.dwH, 2e-15, 4) 
8322          self.assertAlmostEqual(spin135S.kex, 264.055604934724, 4) 
8323          self.assertAlmostEqual(spin135S.chi2, 13.859423588071, 1) 
8324   
8325          # Checks for residue :135F. 
8326          self.assertAlmostEqual(spin135F.r2[r20_key1], 41.4408433837783, 4) 
8327          self.assertAlmostEqual(spin135F.r2[r20_key2], 56.9897267953979, 4) 
8328          self.assertAlmostEqual(spin135F.pA, 0.847378444499757, 4) 
8329          self.assertAlmostEqual(spin135F.dw, 0.856699277665748, 4) 
8330          self.assertAlmostEqual(spin135F.dwH, 5.82587e-10, 4) 
8331          self.assertAlmostEqual(spin135F.kex, 264.055604934724, 4) 
8332          self.assertAlmostEqual(spin135F.chi2, 13.859423588071, 1) 
8333   
8334          # Checks for residue :137S. 
8335          self.assertAlmostEqual(spin137S.r2[r20_key1], 23.0516959385703, 4) 
8336          self.assertAlmostEqual(spin137S.r2[r20_key2], 28.3528064839538, 4) 
8337          self.assertAlmostEqual(spin137S.pA, 0.847378444499757, 4) 
8338          self.assertAlmostEqual(spin137S.dw, 0.772904450844973, 4) 
8339          self.assertAlmostEqual(spin137S.dwH, 0.18335147851297, 4) 
8340          self.assertAlmostEqual(spin137S.kex, 264.055604934724, 4) 
8341          self.assertAlmostEqual(spin137S.chi2, 13.859423588071, 1) 
8342   
8343          # Checks for residue :137F. 
8344          self.assertAlmostEqual(spin137F.r2[r20_key1], 44.7020320742104, 4) 
8345          self.assertAlmostEqual(spin137F.r2[r20_key2], 56.4531460526853, 4) 
8346          self.assertAlmostEqual(spin137F.pA, 0.847378444499757, 4) 
8347          self.assertAlmostEqual(spin137F.dw, 0.984568590342831, 4) 
8348          self.assertAlmostEqual(spin137F.dwH, 2.0931309e-09, 4) 
8349          self.assertAlmostEqual(spin137F.kex, 264.055604934724, 4) 
8350          self.assertAlmostEqual(spin137F.chi2, 13.859423588071, 1) 
8351   
8352   
8353 -    def test_tp02_data_to_ns_r1rho_2site(self, model=None): 
8354          """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 
8355   
8356          # Setup the data. 
8357          self.setup_tp02_data_to_ns_r1rho_2site() 
8358   
8359          # Alias the spins. 
8360          spin1 = cdp.mol[0].res[0].spin[0] 
8361          spin2 = cdp.mol[0].res[1].spin[0] 
8362   
8363          # The R20 keys. 
8364          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8365          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8366   
8367          # Checks for residue :1. 
8368          self.assertAlmostEqual(spin1.r2[r20_key1], 8.50207717367548, 4) 
8369          self.assertAlmostEqual(spin1.r2[r20_key2], 13.4680429589972, 4) 
8370          self.assertAlmostEqual(spin1.pA, 0.864523128842393, 4) 
8371          self.assertAlmostEqual(spin1.dw, 8.85204828994151, 4) 
8372          self.assertAlmostEqual(spin1.kex/1000, 1199.56359549637/1000, 4) 
8373          self.assertAlmostEqual(spin1.chi2, 2.99182130153514, 4) 
8374   
8375          # Checks for residue :2. 
8376          self.assertAlmostEqual(spin2.r2[r20_key1], 10.2099357790203, 4) 
8377          self.assertAlmostEqual(spin2.r2[r20_key2], 16.2137648697873, 4) 
8378          self.assertAlmostEqual(spin2.pA, 0.836488681031685, 4) 
8379          self.assertAlmostEqual(spin2.dw, 9.5505714779503, 4) 
8380          self.assertAlmostEqual(spin2.kex/1000, 1454.45726998929/1000, 4) 
8381          self.assertAlmostEqual(spin2.chi2, 0.000402231563481261, 4) 
8382   
8383   
8384 -    def test_tp02_data_to_ns_r1rho_2site_cluster(self, model=None): 
8385          """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data, when performing clustering.""" 
8386   
8387          # Setup the data. 
8388          self.setup_tp02_data_to_ns_r1rho_2site(clustering=True) 
8389   
8390          # Alias the spins. 
8391          spin1 = cdp.mol[0].res[0].spin[0] 
8392          spin2 = cdp.mol[0].res[1].spin[0] 
8393   
8394          # The R20 keys. 
8395          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8396          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8397   
8398          # Checks for residue :1. 
8399          self.assertAlmostEqual(spin1.r2[r20_key1], 8.48607207881462, 4) 
8400          self.assertAlmostEqual(spin1.r2[r20_key2], 13.4527609061722, 4) 
8401          self.assertAlmostEqual(spin1.pA, 0.863093838784425, 4) 
8402          self.assertAlmostEqual(spin1.dw, 8.86218096536618, 4) 
8403          self.assertAlmostEqual(spin1.kex/1000, 1186.22749648299/1000, 4) 
8404          self.assertAlmostEqual(spin1.chi2, 3.09500996065247, 4) 
8405   
8406          # Checks for residue :2. 
8407          self.assertAlmostEqual(spin2.r2[r20_key1], 10.4577906018883, 4) 
8408          self.assertAlmostEqual(spin2.r2[r20_key2], 16.4455550953792, 4) 
8409          self.assertAlmostEqual(spin2.pA, 0.863093838784425, 4) 
8410          self.assertAlmostEqual(spin2.dw, 11.5841168862587, 4) 
8411          self.assertAlmostEqual(spin2.kex/1000, 1186.22749648299/1000, 4) 
8412          self.assertAlmostEqual(spin2.chi2, 3.09500996065247, 4) 
8413   
8414   
8415 -    def test_tp02_data_to_mp05(self): 
8416          """Test the dispersion 'MP05' model fitting against the 'TP02' test data.""" 
8417   
8418          # Fixed time variable and the models. 
8419          ds.fixed = True 
8420          ds.models = ['R2eff', 'MP05'] 
8421   
8422          # Execute the script. 
8423          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8424   
8425          # Switch back to the data pipe for the optimisation. 
8426          self.interpreter.pipe.switch('MP05 - relax_disp') 
8427   
8428          # The equivalent MP05 parameters. 
8429          r1rho_prime = [[10.0058086343329, 15.005806870124], [12.0766320470785, 18.0767503536277]] 
8430          pA = [0.775055484521586, 0.500000000036595] 
8431          kex = [1235.20361276079, 2378.31403454691] 
8432          delta_omega = [7.08194146569694, 5.4083562844306] 
8433          chi2 = [0.0370400968727768, 0.182141732163934] 
8434   
8435          # Alias the spins. 
8436          spin1 = cdp.mol[0].res[0].spin[0] 
8437          spin2 = cdp.mol[0].res[1].spin[0] 
8438   
8439          # The R20 keys. 
8440          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8441          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8442   
8443          # Printout. 
8444          print("\n\nOptimised parameters:\n") 
8445          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
8446          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
8447          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
8448          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
8449          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
8450          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
8451          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
8452   
8453          # Check each spin. 
8454          spin_index = 0 
8455          for spin, spin_id in spin_loop(return_id=True): 
8456              # Printout. 
8457              print("\nSpin %s." % spin_id) 
8458   
8459              # Check the fitted parameters. 
8460              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8461              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8462              self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 
8463              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8464              self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 
8465              self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 
8466   
8467              # Increment the spin index. 
8468              spin_index += 1 
8469   
8470   
8471 -    def test_tp02_data_to_tap03(self): 
8472          """Test the dispersion 'TAP03' model fitting against the 'TP02' test data.""" 
8473   
8474          # Fixed time variable and the models. 
8475          ds.fixed = True 
8476          ds.models = ['R2eff', 'TAP03'] 
8477   
8478          # Execute the script. 
8479          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8480   
8481          # Switch back to the data pipe for the optimisation. 
8482          self.interpreter.pipe.switch('TAP03 - relax_disp') 
8483   
8484          # The equivalent TAP03 parameters. 
8485          r1rho_prime = [[10.0058156589442, 15.005818505006], [12.0766046472748, 18.076648462452]] 
8486          pA = [0.775042569092891, 0.500000000229685] 
8487          kex = [1235.20852748765, 2379.47085580169] 
8488          delta_omega = [7.08176806468445, 5.40708372863538] 
8489          chi2 = [0.0371366837083293, 0.182212857256044] 
8490   
8491          # Alias the spins. 
8492          spin1 = cdp.mol[0].res[0].spin[0] 
8493          spin2 = cdp.mol[0].res[1].spin[0] 
8494   
8495          # The R20 keys. 
8496          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8497          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8498   
8499          # Printout. 
8500          print("\n\nOptimised parameters:\n") 
8501          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
8502          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
8503          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
8504          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
8505          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
8506          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
8507          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
8508   
8509          # Switch to the 'MP05' model data pipe, then check for each spin. 
8510          self.interpreter.pipe.switch('TAP03 - relax_disp') 
8511          spin_index = 0 
8512          for spin, spin_id in spin_loop(return_id=True): 
8513              # Printout. 
8514              print("\nSpin %s." % spin_id) 
8515   
8516              # Check the fitted parameters. 
8517              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8518              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8519              self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 
8520              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8521              self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 
8522              self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 
8523   
8524              # Increment the spin index. 
8525              spin_index += 1 
8526   
8527   
8528 -    def test_task_7882_monte_carlo_std_residual(self): 
8529          """Implementation of Task #7882 U{https://gna.org/task/?7882}: Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals""" 
8530   
8531          # First check that results are stored with minimisation, to make sure that Sum of Squares are stored (Chi2 without weighting) and degrees of freedom (dof) is stored. 
8532   
8533          # Load the results file from a clustered minimisation. 
8534          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'error_testing'+sep+'task_7882' 
8535          self.interpreter.results.read(file_name) 
8536   
8537          # Get the spins, which was used for clustering. 
8538          spins_cluster = cdp.clustering['sel'] 
8539          spins_free = cdp.clustering['free spins'] 
8540   
8541          # For sanity check, calculate degree of freedom. 
8542          cur_spin_id = spins_cluster[0] 
8543          cur_spin = return_spin(cur_spin_id) 
8544   
8545          # Calculate total number of datapoins. 
8546          N = len(spins_cluster) 
8547          N_dp = N * len(cur_spin.r2eff) 
8548   
8549          # Calculate number of paramaters. For CR72, there is R2 per spectrometer field, individual dw, and shared kex and pA. 
8550          N_par = cdp.spectrometer_frq_count * N + N + 1 + 1 
8551          dof = N_dp - N_par 
8552   
8553          # Sanity check of parameters. 
8554          print(N_par, N_dp) 
8555   
8556          # Number of MC 
8557          mc_nr = 3 
8558   
8559          # Setup MC for errors generated from the distribution described by chi2 and degrees of freedom from best fit. 
8560          self.interpreter.monte_carlo.setup(number=mc_nr) 
8561   
8562          # Create data. 
8563          self.interpreter.monte_carlo.create_data(distribution="red_chi2") 
8564   
8565          # Setup MC again. 
8566          self.interpreter.monte_carlo.setup(number=mc_nr) 
8567   
8568          # Create data, and set the fixed error value, without setting the correct distribution. 
8569          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, fixed_error=1.) 
8570   
8571          # Setup MC again. 
8572          self.interpreter.monte_carlo.setup(number=mc_nr) 
8573   
8574          # Create data, with fixed error distribution, but not setting the error value. 
8575          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, distribution="fixed") 
8576   
8577          # Setup MC again. 
8578          self.interpreter.monte_carlo.create_data(distribution="fixed", fixed_error=1.) 
8579   
8580          # Now select the R2eff model, and try again. Expect raising an error. 
8581          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
8582   
8583          # Setup MC again. 
8584          self.interpreter.monte_carlo.setup(number=mc_nr) 
8585   
8586          # Create data, and assert failure. 
8587          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, distribution="red_chi2") 
8588          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, method="direct", distribution="red_chi2") 
8589   
8590   
8591 -    def x_test_task_7882_kex_conf(self): 
8592          """Test related to Task #7882 U{https://gna.org/task/?7882}: Try making a confidence interval of kex. 
8593          According to the regression book of Graphpad: U{http://www.graphpad.com/faq/file/Prism4RegressionBook.pdf}. 
8594          Page 109-111. 
8595          """ 
8596   
8597          # Load the results file from a clustered minimisation. 
8598          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'error_testing'+sep+'task_7882' 
8599          self.interpreter.results.read(file_name) 
8600   
8601          # Get the spins, which was used for clustering. 
8602          spins_cluster = cdp.clustering['sel'] 
8603          spins_free = cdp.clustering['free spins'] 
8604   
8605          # For sanity check, calculate degree of freedom. 
8606          cur_spin_id = spins_cluster[0] 
8607          cur_spin = return_spin(cur_spin_id) 
8608   
8609          # Calculate total number of datapoins. 
8610          Ns = len(spins_cluster) 
8611          N_dp = Ns * len(cur_spin.r2eff) 
8612   
8613          # Calculate number of paramaters. For CR72, there is R2 per spectrometer field, individual dw, and shared kex and pA. 
8614          N_par = cdp.spectrometer_frq_count * Ns + Ns + 1 + 1 
8615          dof_fit = N_dp - N_par 
8616   
8617          # Assert values. 
8618          self.assertEqual(Ns, 61) 
8619          self.assertEqual(N_dp, 1952) 
8620          self.assertEqual(N_par, 185) 
8621   
8622          # Confidence interval of kex. 
8623          # The number of parameters to check is kex = 1. 
8624          P = 1 
8625          # Number of datapoints 
8626          N = N_dp 
8627          # The degrees of freedom for this confidence interval 
8628          dof_conf = N - P 
8629   
8630          # The critical value of the F distribution with p-value of 0.05 for 95% confidence. 
8631          # Can be calculated with microsoft excel: 
8632          # F=FINV(0,05; P; dof_conf), F=FINV(0,05; P; dof_conf), F=FINV(0,05; 1; 1951)=3,846229551 
8633          # Can also be calculated with: import scipy.stats; scipy.stats.f.isf(0.05, 1, 1951)=3.8462295505435562 
8634          F = 3.8462295505435562 
8635          # Then calculate the scaling of chi2, which is the weighted sum of squares of best fit. 
8636          scale = F*P/dof_conf +1 
8637   
8638          # Get the sum of best fit. 
8639          SSbest_fit = cur_spin.chi2 
8640          SSbest_kex = cur_spin.kex 
8641   
8642          # Get the scaled sum of best fit 
8643          SSall_fixed = SSbest_fit * scale 
8644   
8645          print(SSbest_fit, scale, SSall_fixed) 
8646   
8647          # Now generate a list of kex values to try. 
8648          kex_cur = cur_spin.kex 
8649          kex_list = linspace(kex_cur - 1500, kex_cur + 3000, 200) 
8650   
8651          chi2_list = [] 
8652   
8653          for kex in kex_list: 
8654              self.interpreter.value.set(val=kex, param='kex') 
8655   
8656              # Calculate the chi2 values. 
8657              self.interpreter.minimise.calculate(verbosity=0) 
8658   
8659              # Get the chi2 value 
8660              chi2_cur = cur_spin.chi2 
8661              print("kex=%3.2f, chi2=%3.2f"%(kex, chi2_cur), chi2_cur<SSall_fixed) 
8662   
8663              # Add to list 
8664              chi2_list.append(chi2_cur) 
8665   
8666          # Now make to numpy array. 
8667          chi2_list = asarray(chi2_list) 
8668   
8669          # Now make a selection mask based on the criteria. 
8670          sel_mask = chi2_list < SSall_fixed 
8671   
8672          # Select values of kex, and chi2_list 
8673          kex_sel = kex_list[sel_mask] 
8674          chi2_sel = chi2_list[sel_mask] 
8675   
8676          # Now make plot 
8677          print(SSbest_kex, SSbest_fit, SSall_fixed) 
8678          print(kex_sel) 
8679          print(chi2_sel) 
8680   
8681          if True: 
8682              import matplotlib.pyplot as plt 
8683   
8684              plt.plot(kex_sel, chi2_sel, "bo") 
8685              plt.plot(SSbest_kex, SSbest_fit, "g*") 
8686              plt.show() 
8687   
8688   
8689 -    def test_tp02_data_to_tp02(self): 
8690          """Test the relaxation dispersion 'TP02' model curve fitting to fixed time synthetic data.""" 
8691   
8692          # Fixed time variable. 
8693          ds.fixed = True 
8694   
8695          # Execute the script. 
8696          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8697   
8698          # The original parameters. 
8699          r1rho_prime = [[10.0, 15.0], [12.0, 18.0]] 
8700          pA = 0.7654321 
8701          kex = 1234.56789 
8702          delta_omega = [7.0, 9.0] 
8703   
8704          # The R20 keys. 
8705          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8706          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8707   
8708          # Switch to the 'TP02' model data pipe, then check for each spin. 
8709          self.interpreter.pipe.switch('TP02 - relax_disp') 
8710          spin_index = 0 
8711          for spin, spin_id in spin_loop(return_id=True): 
8712              # Printout. 
8713              print("\nSpin %s." % spin_id) 
8714   
8715              # Check the fitted parameters. 
8716              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8717              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8718              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8719              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 3) 
8720   
8721              # Increment the spin index. 
8722              spin_index += 1 
8723   
8724   
8725 -    def test_value_write_calc_rotating_frame_params_int(self): 
8726          """System test of the value.write function to write intensities for an R1rho setup. 
8727          This system test is to make sure, that modifying the API for special parameters theta and w_eff does not alter the functionality value.write. 
8728   
8729          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8730          """ 
8731   
8732          # Load the state. 
8733          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8734          self.interpreter.state.load(statefile, force=True) 
8735   
8736          # Set filepaths. 
8737          int_filepath = ds.tmpdir+sep+'int.out' 
8738   
8739          # Write out the intensity parameter file. 
8740          # The writing out of intensity file is to make sure the API function retains its function after modification for special parameters. 
8741          self.interpreter.value.write(param='peak_intensity', file='int.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8742   
8743          # Test the file exists. 
8744          self.assert_(access(int_filepath, F_OK)) 
8745   
8746          # Open the files for testing. 
8747          int_file = open(int_filepath, 'r') 
8748   
8749          # Loop over the intensity file to test values. 
8750          for line in int_file: 
8751              # Skip lines starting with #. 
8752              if line[0] == "#": 
8753                  continue 
8754   
8755              # Split the line 
8756              linesplit = line.split() 
8757   
8758              # Assume values 
8759              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8760                  self.assertEqual(linesplit[5], "115571.4") 
8761              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8762                  self.assertEqual(linesplit[5], "68377.52") 
8763              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8764                  self.assertEqual(linesplit[5], "9141.689") 
8765              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8766                  self.assertEqual(linesplit[5], "29123.77") 
8767              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8768                  self.assertEqual(linesplit[5], "58914.94") 
8769   
8770          # Close files 
8771          int_file.close() 
8772   
8773   
8774 -    def test_value_write_calc_rotating_frame_params_theta(self): 
8775          """System test of the value.write function to write return values of theta from calc_rotating_frame_params() function for an R1rho setup. 
8776   
8777          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8778          """ 
8779   
8780          # Load the state. 
8781          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8782          self.interpreter.state.load(statefile, force=True) 
8783   
8784          # Set filepaths. 
8785          theta_filepath = ds.tmpdir+sep+'theta.out' 
8786   
8787          # Write out the theta parameter file. 
8788          self.interpreter.value.write(param='theta', file='theta.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8789   
8790          # Test the file exists. 
8791          self.assert_(access(theta_filepath, F_OK)) 
8792   
8793          # Open the files for testing. 
8794          theta_file = open(theta_filepath, 'r') 
8795   
8796          # Loop over the theta file to test values. 
8797          for line in theta_file: 
8798              # Skip lines starting with #. 
8799              if line[0] == "#": 
8800                  continue 
8801              # Print lines, not including newline character. 
8802              print(line[:-1]) 
8803   
8804              # Split the line 
8805              linesplit = line.split() 
8806   
8807              # Assume values 
8808              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8809                  self.assertNotEqual(linesplit[5], "None") 
8810              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8811                  self.assertNotEqual(linesplit[5], "None") 
8812              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8813                  self.assertNotEqual(linesplit[5], "None") 
8814              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8815                  self.assertNotEqual(linesplit[5], "None") 
8816              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8817                  self.assertNotEqual(linesplit[5], "None") 
8818   
8819          # Close files 
8820          theta_file.close() 
8821   
8822   
8823 -    def test_value_write_calc_rotating_frame_params_w_eff(self): 
8824          """System test of the value.write function to write return values of w_eff from calc_rotating_frame_params() function for an R1rho setup. 
8825   
8826          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8827          """ 
8828   
8829          # Load the state. 
8830          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8831          self.interpreter.state.load(statefile, force=True) 
8832   
8833          # Set filepaths. 
8834          w_eff_filepath = ds.tmpdir+sep+'w_eff.out' 
8835   
8836          # Write out the w_eff parameter file. 
8837          self.interpreter.value.write(param='w_eff', file='w_eff.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8838   
8839          # Test the file exists. 
8840          self.assert_(access(w_eff_filepath, F_OK)) 
8841   
8842          # Open the files for testing. 
8843          w_eff_file = open(w_eff_filepath, 'r') 
8844   
8845          # Loop over the w_eff file to test values. 
8846          for line in w_eff_file: 
8847              # Skip lines starting with #. 
8848              if line[0] == "#": 
8849                  continue 
8850              # Print lines, not including newline character. 
8851              print(line[:-1]) 
8852   
8853              # Split the line 
8854              linesplit = line.split() 
8855   
8856              # Assume values 
8857              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8858                  self.assertNotEqual(linesplit[5], "None") 
8859              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8860                  self.assertNotEqual(linesplit[5], "None") 
8861              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8862                  self.assertNotEqual(linesplit[5], "None") 
8863              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8864                  self.assertNotEqual(linesplit[5], "None") 
8865              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8866                  self.assertNotEqual(linesplit[5], "None") 
8867   
8868          # Close files 
8869          w_eff_file.close() 
8870   
8871   
8872 -    def test_value_write_calc_rotating_frame_params_auto_analysis(self): 
8873          """System test of the auto_analysis value.write function to write theta and w_eff values for an R1rho setup. 
8874   
8875          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8876          """ 
8877   
8878          # Load the state. 
8879          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344.bz2' 
8880          self.interpreter.state.load(statefile, force=True) 
8881   
8882          # Set pipe name, bundle and type. 
8883          pipe_name = 'base pipe' 
8884          pipe_bundle = 'relax_disp' 
8885          pipe_type = 'relax_disp' 
8886   
8887          # The path to the data files. 
8888          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
8889   
8890          # Deselect all spins 
8891          self.interpreter.deselect.all() 
8892   
8893          # Specify spins to be selected. 
8894          select_spin_ids = [ 
8895          ":13@N", 
8896          ":15@N", 
8897          ":16@N", 
8898          ":25@N", 
8899          ":26@N", 
8900          ":28@N", 
8901          ":39@N", 
8902          ":40@N", 
8903          ":41@N", 
8904          ":43@N", 
8905          ":44@N", 
8906          ":45@N", 
8907          ":49@N", 
8908          ":52@N", 
8909          ":53@N"] 
8910   
8911          # Reverse the selection for the spins. 
8912          for curspin in select_spin_ids: 
8913              print("Selecting spin %s"%curspin) 
8914              self.interpreter.deselect.reverse(spin_id=curspin) 
8915   
8916          # Read the R1 data 
8917          self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
8918   
8919          # The dispersion models. 
8920          MODELS = ['R2eff'] 
8921   
8922          # The grid search size (the number of increments per dimension). 
8923          GRID_INC = 4 
8924   
8925          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
8926          MC_NUM = 3 
8927   
8928          # Model selection technique. 
8929          MODSEL = 'AIC' 
8930   
8931          # Execute the auto-analysis (fast). 
8932          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
8933          OPT_FUNC_TOL = 1e-1 
8934          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
8935          OPT_MAX_ITERATIONS = 1000 
8936          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
8937   
8938          # Run the analysis. 
8939          relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=ds.tmpdir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
8940   
8941          ## Check for file creation 
8942          # Set filepaths. 
8943          theta_filepath = ds.tmpdir+sep+MODELS[0]+sep+'theta.out' 
8944          w_eff_filepath = ds.tmpdir+sep+MODELS[0]+sep+'w_eff.out' 
8945   
8946          # Test the files exists. 
8947          self.assert_(access(theta_filepath, F_OK)) 
8948          self.assert_(access(w_eff_filepath, F_OK)) 
8949   
8950          # Open the files for testing. 
8951          theta_file = open(theta_filepath, 'r') 
8952          theta_result = [ 
8953              "# Parameter description:  Rotating frame tilt angle : ( theta = arctan(w_1 / Omega) ) (rad).\n", 
8954              "#\n", 
8955              "# mol_name    res_num    res_name    spin_num    spin_name    r1rho_799.77739910_118.078_1341.110    sd(r1rho_799.77739910_118.078_1341.110)    r1rho_799.77739910_118.078_1648.500    sd(r1rho_799.77739910_118.078_1648.500)    r1rho_799.77739910_118.078_431.000    sd(r1rho_799.77739910_118.078_431.000)    r1rho_799.77739910_118.078_651.200    sd(r1rho_799.77739910_118.078_651.200)    r1rho_799.77739910_118.078_800.500    sd(r1rho_799.77739910_118.078_800.500)    r1rho_799.77739910_118.078_984.000    sd(r1rho_799.77739910_118.078_984.000)    r1rho_799.77739910_124.247_1341.110    sd(r1rho_799.77739910_124.247_1341.110)    r1rho_799.77739910_130.416_1341.110    sd(r1rho_799.77739910_130.416_1341.110)    r1rho_799.77739910_130.416_1648.500    sd(r1rho_799.77739910_130.416_1648.500)    r1rho_799.77739910_130.416_800.500    sd(r1rho_799.77739910_130.416_800.500)    r1rho_799.77739910_142.754_1341.110    sd(r1rho_799.77739910_142.754_1341.110)    r1rho_799.77739910_142.754_800.500    sd(r1rho_799.77739910_142.754_800.500)    r1rho_799.77739910_179.768_1341.110    sd(r1rho_799.77739910_179.768_1341.110)    r1rho_799.77739910_241.459_1341.110    sd(r1rho_799.77739910_241.459_1341.110)    \n", 
8956              "None          5          I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8957              "None          6          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8958              "None          8          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8959              "None          9          A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8960              "None          10         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8961              "None          11         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8962              "None          12         D           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8963              "None          13         L           None        N                1.83827367612531                   None                                           1.79015307643158                   None                                            2.2768687598681                  None                                          2.08461171779445                  None                                          2.00120623474388                  None                                          1.92825070277699                  None                                          1.47212860033516                   None                                           1.12978017906854                   None                                           1.20415336139956                   None                                          0.901691390796334                  None                                         0.687390207543568                   None                                          0.455635480573046                  None                                         0.281637123971289                   None                                          0.138259661766539                   None                                       \n", 
8964              "None          14         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8965              "None          15         R           None        N                1.58367544790673                   None                                           1.58127411936947                   None                                           1.61085209029811                  None                                          1.59731540507347                  None                                          1.59237108385522                  None                                          1.58834866344307                  None                                           1.2251048782537                   None                                          0.938142786712004                   None                                           1.03297495592991                   None                                          0.683284686224254                  None                                         0.594447788256641                   None                                          0.383528609383686                  None                                         0.262780814059893                   None                                          0.133469839450564                   None                                       \n", 
8966              "None          16         T           None        N                1.40984232256624                   None                                           1.43947245672073                   None                                           1.10299856647417                  None                                          1.24811470332083                  None                                          1.30521602599932                  None                                          1.35302443831853                  None                                          1.07923777467974                   None                                          0.833345927788896                   None                                          0.934350308974616                   None                                          0.581325254389991                  None                                         0.543659670184793                   None                                          0.346238480454282                  None                                         0.251454336191817                   None                                          0.130436714663781                   None                                       \n", 
8967              "None          17         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8968              "None          18         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8969              "None          19         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8970              "None          21         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8971              "None          24         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8972              "None          25         Q           None        N                1.81569700258844                   None                                           1.77137827615015                   None                                           2.23175875585624                  None                                          2.04612705363098                  None                                           1.9673155780155                  None                                          1.89908711012298                  None                                          1.44829660124856                   None                                           1.11023386429581                   None                                           1.18716091371256                   None                                          0.877306975624962                  None                                         0.677790118853413                   None                                          0.447932002242236                  None                                         0.279785379050945                   None                                          0.137802891887767                   None                                       \n", 
8973              "None          26         Q           None        N                1.61128821168674                   None                                           1.60374392042003                   None                                           1.69619923953765                  None                                          1.65403989292986                  None                                          1.63856717205868                  None                                          1.62595755714564                  None                                          1.24977859227795                   None                                          0.956353494917591                   None                                           1.04972090035774                   None                                          0.702164059520172                  None                                         0.603227813742091                   None                                          0.390116910781037                  None                                         0.264658552037535                   None                                          0.133960994297096                   None                                       \n", 
8974              "None          27         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8975              "None          28         Q           None        N                1.65182797011356                   None                                           1.63676707684161                   None                                           1.81830827892972                  None                                           1.7365089711986                  None                                          1.70601955220877                  None                                          1.68102938663686                  None                                          1.28685736157369                   None                                          0.984047498595701                   None                                            1.0749792109454                   None                                          0.731585685663053                  None                                         0.616577997665602                   None                                          0.400219205533665                  None                                         0.267471993812649                   None                                          0.134690869499646                   None                                       \n", 
8976              "None          29         V           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8977              "None          30         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8978              "None          31         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8979              "None          32         I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8980              "None          33         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8981              "None          34         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8982              "None          35         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8983              "None          36         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8984              "None          38         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8985              "None          39         L           None        N                1.76426439181176                   None                                           1.72885318885161                   None                                           2.11826300085737                  None                                          1.95430201082222                  None                                          1.88794717058464                  None                                          1.83172922971397                  None                                          1.39549951193417                   None                                           1.06783946148624                   None                                           1.14997013232702                   None                                          0.826128785942585                  None                                         0.657105386950171                   None                                          0.431542911580536                  None                                         0.275725736430539                   None                                          0.136791385554619                   None                                       \n", 
8986              "None          40         M           None        N                 1.5521741199158                   None                                           1.55564594516135                   None                                           1.51290906497298                  None                                          1.53245929150759                  None                                          1.53960430408466                  None                                          1.54541832596591                  None                                          1.19750223001929                   None                                          0.917959090226757                   None                                           1.01428385962747                   None                                          0.662779584695967                  None                                         0.584708929219264                   None                                          0.376271266885303                  None                                         0.260671619214194                   None                                          0.132914250767089                   None                                       \n", 
8987              "None          41         A           None        N                1.68339451828261                   None                                           1.66252964414082                   None                                           1.90911961276946                  None                                          1.79959323497326                  None                                          1.75801925517113                  None                                          1.72370710837265                  None                                          1.31646868936419                   None                                           1.00647189763597                   None                                           1.09525348649914                   None                                           0.75605702767542                  None                                         0.627395557358039                   None                                          0.408481831044309                  None                                         0.269716174238842                   None                                          0.135267948387412                   None                                       \n", 
8988              "None          42         A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8989              "None          43         F           None        N                1.58506597154432                   None                                           1.58240542750303                   None                                           1.61517196062351                  None                                          1.60017740004898                  None                                          1.59469990835425                  None                                          1.59024353162528                  None                                          1.22633651794829                   None                                          0.939047922181951                   None                                           1.03380990731605                   None                                          0.684214484755514                  None                                         0.594884298549546                   None                                          0.383855128702894                  None                                         0.262874695048502                   None                                           0.13349447283116                   None                                       \n", 
8990              "None          44         I           None        N                1.57575471961837                   None                                           1.57483015671791                   None                                           1.58622388390755                  None                                          1.58100758841935                  None                                          1.57910319967536                  None                                          1.57755415552211                  None                                          1.21811077066835                   None                                          0.933010299763027                   None                                           1.02823520295828                   None                                           0.67802911457195                  None                                         0.591972285081647                   None                                          0.381678892926696                  None                                         0.262247347241724                   None                                          0.133329708422379                   None                                       \n", 
8991              "None          45         K           None        N                1.77147501495754                   None                                           1.73479633022489                   None                                           2.13509660780385                  None                                          1.96751045408372                  None                                          1.89924480319914                  None                                          1.84124387452692                  None                                          1.40277881643715                   None                                           1.07361367582571                   None                                           1.15506365550891                   None                                          0.832963505534767                  None                                         0.659913187081268                   None                                          0.433751178249555                  None                                         0.276282572106685                   None                                           0.13693095791902                   None                                       \n", 
8992              "None          46         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8993              "None          48         T           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8994              "None          49         A           None        N                2.00297059962685                   None                                           1.92978318052058                   None                                           2.53305709323468                  None                                          2.33052197276846                  None                                          2.22870514722639                  None                                          2.13201782446864                  None                                           1.6587904412969                   None                                           1.29333162369472                   None                                           1.34311052758116                   None                                           1.12559033900783                  None                                         0.770195063841652                   None                                          0.524846264860003                  None                                         0.296857751274362                   None                                          0.141908833673671                   None                                       \n", 
8995              "None          50         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8996              "None          51         Y           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8997              "None          52         V           None        N                1.82421571143794                   None                                           1.77845404105203                   None                                           2.24910726268822                  None                                          2.06078232916932                  None                                          1.98017451806059                  None                                          1.91012195713554                  None                                          1.45724107606646                   None                                           1.11753869321304                   None                                           1.19352234944057                   None                                          0.886361068343012                  None                                         0.681372607920812                   None                                          0.450799407357501                  None                                         0.280478735779163                   None                                          0.137974257665877                   None                                       \n", 
8998              "None          53         A           None        N                2.05019708195234                   None                                           1.97089957318506                   None                                           2.58789168363698                  None                                          2.39027806684801                  None                                          2.28731354878582                  None                                           2.1872118539319                  None                                           1.7165709935896                   None                                           1.34832362477229                   None                                           1.38879751095815                   None                                            1.2085314357749                  None                                         0.799450059125864                   None                                          0.550583841461621                  None                                          0.30195492609136                   None                                          0.143090604877102                   None                                       \n", 
8999              "None          54         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9000              "None          55         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9001              "None          57         G           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9002              "None          58         M           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9003              "None          59         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n" 
9004          ] 
9005          # Check the created theta file. 
9006          lines = theta_file.readlines() 
9007          for i in range(len(lines)): 
9008              # Test lines starting with # 
9009              if theta_result[i][0] == "#": 
9010                  self.assertEqual(theta_result[i], lines[i]) 
9011              # If the line is equal each other, make a line comparison. This should catch lines with None values. 
9012              if theta_result[i] == lines[i]: 
9013                  self.assertEqual(theta_result[i], lines[i]) 
9014              # If the line is not equal each other, make a slower comparison of values. 
9015              else: 
9016                  # Print lines if they don't match. To help find differences. 
9017                  print(theta_result[i]) 
9018                  print(lines[i]) 
9019   
9020                  # First test first 62 characters containing spin information 
9021                  self.assertEqual(theta_result[i][:62], lines[i][:62]) 
9022   
9023                  # Make a string split after 62 characters. Select each second element, so None values are skipped. 
9024                  theta_result_s = theta_result[i][62:].split()[::2] 
9025                  print(theta_result_s ) 
9026                  lines_s = lines[i][62:].split()[::2] 
9027                  print(lines_s) 
9028                  # Loop over the value elements 
9029                  for j in range(len(lines_s)): 
9030                      print(theta_result_s[j], lines_s[j]) 
9031                      # Assume a precision to digits. 
9032                      self.assertAlmostEqual(float(theta_result_s[j]), float(lines_s[j]), 14) 
9033   
9034          # Close file 
9035          theta_file.close() 
9036   
9037          w_eff_file = open(w_eff_filepath, 'r') 
9038          w_eff_result = [ 
9039              "# Parameter description:  Effective field in rotating frame : ( w_eff = sqrt(Omega^2 + w_1^2) ) (rad.s^-1).\n", 
9040              "#\n", 
9041              "# mol_name    res_num    res_name    spin_num    spin_name    r1rho_799.77739910_118.078_1341.110    sd(r1rho_799.77739910_118.078_1341.110)    r1rho_799.77739910_118.078_1648.500    sd(r1rho_799.77739910_118.078_1648.500)    r1rho_799.77739910_118.078_431.000    sd(r1rho_799.77739910_118.078_431.000)    r1rho_799.77739910_118.078_651.200    sd(r1rho_799.77739910_118.078_651.200)    r1rho_799.77739910_118.078_800.500    sd(r1rho_799.77739910_118.078_800.500)    r1rho_799.77739910_118.078_984.000    sd(r1rho_799.77739910_118.078_984.000)    r1rho_799.77739910_124.247_1341.110    sd(r1rho_799.77739910_124.247_1341.110)    r1rho_799.77739910_130.416_1341.110    sd(r1rho_799.77739910_130.416_1341.110)    r1rho_799.77739910_130.416_1648.500    sd(r1rho_799.77739910_130.416_1648.500)    r1rho_799.77739910_130.416_800.500    sd(r1rho_799.77739910_130.416_800.500)    r1rho_799.77739910_142.754_1341.110    sd(r1rho_799.77739910_142.754_1341.110)    r1rho_799.77739910_142.754_800.500    sd(r1rho_799.77739910_142.754_800.500)    r1rho_799.77739910_179.768_1341.110    sd(r1rho_799.77739910_179.768_1341.110)    r1rho_799.77739910_241.459_1341.110    sd(r1rho_799.77739910_241.459_1341.110)    \n", 
9042              "None          5          I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9043              "None          6          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9044              "None          8          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9045              "None          9          A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9046              "None          10         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9047              "None          11         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9048              "None          12         D           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9049              "None          13         L           None        N                8737.12883908829                   None                                           10612.1226552258                   None                                           3558.93734069587                  None                                          4698.27194621826                  None                                          5534.46153956037                  None                                          6599.82570817753                  None                                          8467.62674839481                   None                                           9318.00441649087                   None                                           11095.2662520767                   None                                           6412.33580591254                  None                                          13279.9803044242                   None                                            11430.254637056                  None                                          30318.7268264644                   None                                           61141.1080046448                   None                                       \n", 
9050              "None          14         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9051              "None          15         R           None        N                8427.14155005377                   None                                           10358.3995676635                   None                                           2710.22680763322                  None                                          4093.04942975722                  None                                          5030.86065069262                  None                                          6183.60685459024                  None                                          8956.28403254202                   None                                           10448.6627754369                   None                                           12060.4428066937                   None                                           7966.64282975241                  None                                          15045.8392092364                   None                                           13441.3586252373                  None                                          32438.4764809909                   None                                           63321.5201471181                   None                                       \n", 
9052              "None          16         T           None        N                 8536.7818857229                   None                                            10447.792678989                   None                                           3034.01707453628                  None                                           4314.2767521567                  None                                          5212.43600885913                  None                                          6332.21319855067                  None                                          9558.14311447582                   None                                           11384.2336494604                   None                                           12879.4604966293                   None                                           9159.34604475399                  None                                          16290.1746838959                   None                                           14821.0200530829                  None                                          33866.5933527757                   None                                           64785.3205696403                   None                                       \n", 
9053              "None          17         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9054              "None          18         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9055              "None          19         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9056              "None          21         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9057              "None          24         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9058              "None          25         Q           None        N                8685.60895531182                   None                                           10569.7459677762                   None                                           3430.51272680396                  None                                          4601.75421490393                  None                                          5452.76508815826                  None                                          6531.46859076009                  None                                          8490.06475886501                   None                                           9406.58372902508                   None                                           11169.7602637607                   None                                           6540.38696356753                  None                                          13437.7348017798                   None                                           11613.1632549021                  None                                          30514.0741594726                   None                                           61342.4792156782                   None                                       \n", 
9059              "None          26         Q           None        N                8433.35533683544                   None                                           10363.4554631194                   None                                           2729.48656005151                  None                                          4105.82770792005                  None                                          5041.26238350827                  None                                          6192.07245313098                  None                                          8880.08366342131                   None                                           10312.6868786802                   None                                           11942.8320576165                   None                                           7787.44854491812                  None                                          14853.4987024375                   None                                           13225.7048162038                  None                                          32213.6690023282                   None                                           63090.7407990801                   None                                       \n", 
9060              "None          27         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9061              "None          28         Q           None        N                8454.18308422202                   None                                           10380.4112885894                   None                                           2793.17494362899                  None                                          4148.43953208179                  None                                          5076.02756135055                  None                                          6220.40920270029                  None                                          8777.91538040813                   None                                           10118.8737706315                   None                                           11775.8792998529                   None                                           7528.90766101027                  None                                          14572.4015102398                   None                                            12909.211050939                  None                                          31882.8171856889                   None                                           62750.9120842199                   None                                       \n", 
9062              "None          29         V           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9063              "None          30         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9064              "None          31         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9065              "None          32         I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9066              "None          33         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9067              "None          34         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9068              "None          35         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9069              "None          36         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9070              "None          38         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9071              "None          39         L           None        N                 8586.6405431352                   None                                           10488.5710521378                   None                                           3171.59430904777                  None                                          4412.11227722123                  None                                          5293.69814015286                  None                                          6399.27143075725                  None                                          8557.58926327909                   None                                           9617.45773774313                   None                                           11347.9169998729                   None                                           6840.20010813426                  None                                          13795.1250622375                   None                                           12024.9041436853                  None                                           30951.651485352                   None                                           61793.2130509111                   None                                       \n", 
9072              "None          40         M           None        N                8427.90394711227                   None                                           10359.0198301036                   None                                           2712.59646573568                  None                                          4094.61889210019                  None                                          5032.13762965554                  None                                           6184.6458240746                  None                                          9049.68452800053                   None                                           10607.7913029633                   None                                           12198.5639821231                   None                                           8174.23271685285                  None                                          15266.4924700447                   None                                           13687.9010998756                  None                                          32694.9043143038                   None                                           63584.6371927381                   None                                       \n", 
9073              "None          41         A           None        N                8480.14299737436                   None                                           10401.5648897003                   None                                           2870.79081440785                  None                                          4201.09083283266                  None                                          5119.14733505123                  None                                          6255.64579267482                  None                                          8706.50768957471                   None                                           9972.71017314947                   None                                           11650.5225246067                   None                                           7331.28858930568                  None                                          14354.1616183112                   None                                           12662.3378547029                  None                                          31623.9195264738                   None                                           62484.8290612112                   None                                       \n", 
9074              "None          42         A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9075              "None          43         F           None        N                8427.30062786474                   None                                           10358.5289868368                   None                                            2710.7214015056                  None                                          4093.37694357637                  None                                          5031.12711571215                  None                                          6183.82364721878                  None                                          8952.31975962078                   None                                           10441.7375680915                   None                                           12054.4435931163                   None                                           7957.55789315654                  None                                          15036.1316712316                   None                                           13430.4914212645                  None                                          32427.1596037519                   None                                           63309.9050677925                   None                                       \n", 
9076              "None          44         I           None        N                8426.54623319716                   None                                           10357.9152496503                   None                                            2708.3751705368                  None                                          4091.82359712664                  None                                          5029.86337809029                  None                                          6182.79552045043                  None                                          8979.12144335458                   None                                           10488.2688526334                   None                                           12094.7720286018                   None                                           8018.51779989075                  None                                          15101.1843990883                   None                                           13503.2816173444                  None                                          32502.9389163062                   None                                           63387.6763306952                   None                                       \n", 
9077              "None          45         K           None        N                8599.01176345321                   None                                           10498.7013581079                   None                                           3204.93649737055                  None                                          4436.14046641897                  None                                          5313.74138343704                  None                                          6415.86177652694                  None                                          8546.79665373249                   None                                           9587.16245449134                   None                                           11322.2529042385                   None                                           6797.53838612575                  None                                          13745.1536613763                   None                                           11967.5433300612                  None                                          30890.8603419261                   None                                           61730.6213936947                   None                                       \n", 
9078              "None          46         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9079              "None          48         T           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9080              "None          49         A           None        N                9279.63849130869                   None                                           11063.0654625247                   None                                           4737.11992391463                  None                                          5643.40583860235                  None                                          6356.45614406507                  None                                          7302.87406141381                  None                                          8459.17105047661                   None                                           8761.54554569995                   None                                           10632.2343488142                   None                                           5572.92782399155                  None                                          12102.1714908775                   None                                           10037.6988885228                  None                                          28806.6916858172                   None                                           59579.0348769179                   None                                       \n", 
9081              "None          50         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9082              "None          51         Y           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9083              "None          52         V           None        N                8704.45610117774                   None                                           10585.2389163429                   None                                            3477.9549539207                  None                                          4637.22923167743                  None                                          5482.73656118686                  None                                           6556.5108895527                  None                                          8481.06470969555                   None                                           9372.86414918436                   None                                           11141.3782476763                   None                                           6491.79686536093                  None                                          13378.2843939736                   None                                           11544.3205736882                  None                                            30440.62308788                   None                                           61266.7742546508                   None                                       \n", 
9084              "None          53         A           None        N                9497.02860450276                   None                                           11246.0339326126                   None                                           5149.96766581255                  None                                          5994.15475647208                  None                                          6669.81232845336                  None                                          7577.19152075731                  None                                          8516.77431951689                   None                                           8639.36099840319                   None                                           10531.7750336522                   None                                           5378.79193153767                  None                                          11752.8060152439                   None                                           9613.59939949642                  None                                          28334.9153747994                   None                                           59090.2988815445                   None                                       \n", 
9085              "None          54         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9086              "None          55         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9087              "None          57         G           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9088              "None          58         M           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9089              "None          59         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n" 
9090          ] 
9091          # Check the created w_eff file. 
9092          lines = w_eff_file.readlines() 
9093          for i in range(len(lines)): 
9094              # Test lines starting with # 
9095              if w_eff_result[i][0] == "#": 
9096                  self.assertEqual(w_eff_result[i], lines[i]) 
9097              # If the line is equal each other, make a line comparison. This should catch lines with None values. 
9098              if w_eff_result[i] == lines[i]: 
9099                  self.assertEqual(w_eff_result[i], lines[i]) 
9100              # If the line is not equal each other, make a slower comparison of values. 
9101              else: 
9102                  # Print lines if they don't match. To help find differences. 
9103                  print(w_eff_result[i]) 
9104                  print(lines[i]) 
9105   
9106                  # First test first 62 characters containing spin information 
9107                  self.assertEqual(w_eff_result[i][:62], lines[i][:62]) 
9108   
9109                  # Make a string split after 62 characters. Select each second element, so None values are skipped. 
9110                  w_eff_result_s = w_eff_result[i][62:].split()[::2] 
9111                  print(w_eff_result_s ) 
9112                  lines_s = lines[i][62:].split()[::2] 
9113                  print(lines_s) 
9114                  # Loop over the value elements 
9115                  for j in range(len(lines_s)): 
9116                      print(w_eff_result_s[j], lines_s[j]) 
9117                      # Assume a precision to digits. 
9118                      self.assertAlmostEqual(float(w_eff_result_s[j]), float(lines_s[j]), 14) 
9119   
9120          # Close file 
9121          w_eff_file.close() 
9122   
9123   
9124 -    def verify_estimate_r2eff_err_compare_mc(self): 
9125          """Test the user function for estimating R2eff errors from exponential curve fitting, and compare it with Monte-Carlo simulations. 
9126   
9127          This follows Task 7822. 
9128          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
9129   
9130          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
9131          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
9132          """ 
9133   
9134          # Load the data. 
9135          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep 
9136   
9137          # Set pipe name, bundle and type. 
9138          pipe_name = 'base pipe' 
9139          pipe_bundle = 'relax_disp' 
9140          pipe_type = 'relax_disp' 
9141   
9142          # Create the data pipe. 
9143          self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 
9144   
9145          file = data_path + '1_setup_r1rho_GUI.py' 
9146          self.interpreter.script(file=file, dir=None) 
9147   
9148          # Deselect all spins. 
9149          self.interpreter.deselect.spin(spin_id=':1-100', change_all=False) 
9150   
9151          # Select one spin. 
9152          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
9153   
9154          # Set the model. 
9155          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
9156   
9157          # Check if intensity errors have already been calculated. 
9158          check_intensity_errors() 
9159   
9160          # Do a grid search. 
9161          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=11, constraints=True, verbosity=1) 
9162   
9163          # Set algorithm. 
9164          min_algor = 'Newton' 
9165          constraints = True 
9166          if constraints: 
9167              min_options = ('%s'%(min_algor),) 
9168              #min_algor = 'Log barrier' 
9169              min_algor = 'Method of Multipliers' 
9170              scaling_matrix = assemble_scaling_matrix(scaling=True) 
9171   
9172              # Collect spins 
9173              all_spin_ids = [] 
9174              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9175                  all_spin_ids.append(spin_id) 
9176   
9177              spins = spin_ids_to_containers(all_spin_ids[:1]) 
9178   
9179              # Get constraints 
9180              A, b = linear_constraints(spins=spins, scaling_matrix=scaling_matrix[0]) 
9181          else: 
9182              min_options = () 
9183              A, b = None, None 
9184          min_options = () 
9185          sim_boot = 200 
9186          scaling_list = [1.0, 1.0] 
9187   
9188          # Minimise. 
9189          self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints, verbosity=1) 
9190   
9191          # Loop over old err attributes. 
9192          err_attr_list = ['r2eff_err', 'i0_err'] 
9193   
9194          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9195              # Loop over old err attributes. 
9196              for err_attr in err_attr_list: 
9197                  if hasattr(cur_spin, err_attr): 
9198                      delattr(cur_spin, err_attr) 
9199   
9200          # Collect the estimation data from boot. 
9201          my_dic = {} 
9202          param_key_list = [] 
9203          est_keys = [] 
9204          est_key = '-2' 
9205          est_keys.append(est_key) 
9206          spin_id_list = [] 
9207   
9208          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9209              # Add key to dic. 
9210              my_dic[spin_id] = {} 
9211   
9212              # Add key for estimate. 
9213              my_dic[spin_id][est_key] = {} 
9214   
9215              # Add spin key to list. 
9216              spin_id_list.append(spin_id) 
9217   
9218              # Generate spin string. 
9219              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9220   
9221              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9222                  # Generate the param_key. 
9223                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9224   
9225                  # Append key. 
9226                  param_key_list.append(param_key) 
9227   
9228                  # Add key to dic. 
9229                  my_dic[spin_id][est_key][param_key] = {} 
9230   
9231                  values = [] 
9232                  errors = [] 
9233                  times = [] 
9234                  for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
9235                      values.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)) 
9236                      errors.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)) 
9237                      times.append(time) 
9238   
9239                  # Convert to numpy array. 
9240                  values = asarray(values) 
9241                  errors = asarray(errors) 
9242                  times = asarray(times) 
9243   
9244                  r2eff = getattr(cur_spin, 'r2eff')[param_key] 
9245                  i0 = getattr(cur_spin, 'i0')[param_key] 
9246   
9247                  R_m_sim_l = [] 
9248                  I0_m_sim_l = [] 
9249                  for j in range(sim_boot): 
9250                      if j in range(0, 100000, 100): 
9251                          print("Simulation %i"%j) 
9252                      # Start minimisation. 
9253   
9254                      # Produce errors 
9255                      I_err = [] 
9256                      for j, error in enumerate(errors): 
9257                          I_error = gauss(values[j], error) 
9258                          I_err.append(I_error) 
9259                      # Convert to numpy array. 
9260                      I_err = asarray(I_err) 
9261   
9262                      x0 = [r2eff, i0] 
9263                      model = Relax_fit_opt(num_params=len(x0), values=I_err, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
9264   
9265                      # Ref input. 
9266                      #def generic_minimise(func=None, dfunc=None, d2func=None, args=(), x0=None, min_algor=None, min_options=None, func_tol=1e-25, grad_tol=None, maxiter=1e6, A=None, b=None, l=None, u=None, c=None, dc=None, d2c=None, print_flag=0, print_prefix="", full_output=False): 
9267                      # l=l, u=u, c=c, dc=dc, d2c=d2c 
9268                      # l: Lower bound constraint vector (l <= x <= u). 
9269                      # u: Upper bound constraint vector (l <= x <= u). 
9270                      # c: User supplied constraint function. 
9271                      # dc: User supplied constraint gradient function. 
9272                      params_minfx_sim_j, chi2_minfx_sim_j, iter_count, f_count, g_count, h_count, warning = generic_minimise(func=model.func, dfunc=model.dfunc, d2func=model.d2func, args=(), x0=x0, min_algor=min_algor, min_options=min_options, A=A, b=b, full_output=True, print_flag=0) 
9273   
9274                      R_m_sim_j, I0_m_sim_j = params_minfx_sim_j 
9275                      R_m_sim_l.append(R_m_sim_j) 
9276                      I0_m_sim_l.append(I0_m_sim_j) 
9277   
9278                  # Get stats on distribution. 
9279                  sigma_R_sim = std(asarray(R_m_sim_l), ddof=1) 
9280                  sigma_I0_sim = std(asarray(I0_m_sim_l), ddof=1) 
9281                  my_dic[spin_id][est_key][param_key]['r2eff_err'] = sigma_R_sim 
9282                  my_dic[spin_id][est_key][param_key]['i0_err'] = sigma_I0_sim 
9283   
9284          # Estimate R2eff errors. 
9285          self.interpreter.relax_disp.r2eff_err_estimate() 
9286   
9287          est_key = '-1' 
9288          est_keys.append(est_key) 
9289   
9290          # Collect data. 
9291          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9292              # Add key for estimate. 
9293              my_dic[spin_id][est_key] = {} 
9294   
9295              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9296                  # Generate the param_key. 
9297                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9298   
9299                  # Add key to dic. 
9300                  my_dic[spin_id][est_key][param_key] = {} 
9301   
9302                  # Get the value. 
9303                  # Loop over err attributes. 
9304                  for err_attr in err_attr_list: 
9305                      if hasattr(cur_spin, err_attr): 
9306                          get_err_attr = getattr(cur_spin, err_attr)[param_key] 
9307                      else: 
9308                          get_err_attr = 0.0 
9309   
9310                      # Save to dic. 
9311                      my_dic[spin_id][est_key][param_key][err_attr] = get_err_attr 
9312   
9313   
9314          # Make Carlo Simulations number 
9315          mc_number_list = list(range(0, 1000, 250)) 
9316   
9317          sim_attr_list = ['chi2_sim', 'f_count_sim', 'g_count_sim', 'h_count_sim', 'i0_sim', 'iter_sim', 'peak_intensity_sim', 'r2eff_sim', 'select_sim', 'warning_sim'] 
9318   
9319          # Loop over the Monte Carlo simulations: 
9320          for number in mc_number_list: 
9321              # First delete old simulations. 
9322              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9323                  # Loop over old err attributes. 
9324                  for err_attr in err_attr_list: 
9325                      if hasattr(cur_spin, err_attr): 
9326                          delattr(cur_spin, err_attr) 
9327   
9328                  # Loop over the simulated attributes. 
9329                  for sim_attr in sim_attr_list: 
9330                      if hasattr(cur_spin, sim_attr): 
9331                          delattr(cur_spin, sim_attr) 
9332   
9333              self.interpreter.monte_carlo.setup(number=number) 
9334              self.interpreter.monte_carlo.create_data() 
9335              self.interpreter.monte_carlo.initial_values() 
9336              self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints) 
9337              self.interpreter.eliminate() 
9338              self.interpreter.monte_carlo.error_analysis() 
9339   
9340              est_key = '%i'%number 
9341              est_keys.append(est_key) 
9342   
9343              # Collect data. 
9344              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9345                  # Add key for estimate. 
9346                  my_dic[spin_id][est_key] = {} 
9347   
9348                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9349                      # Generate the param_key. 
9350                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9351   
9352                      # Add key to dic. 
9353                      my_dic[spin_id][est_key][param_key] = {} 
9354   
9355                      # Get the value. 
9356                      # Loop over err attributes. 
9357                      for err_attr in err_attr_list: 
9358                          if hasattr(cur_spin, err_attr): 
9359                              get_err_attr = getattr(cur_spin, err_attr)[param_key] 
9360                          else: 
9361                              get_err_attr = 0.0 
9362   
9363                          # Save to dic. 
9364                          my_dic[spin_id][est_key][param_key][err_attr] = get_err_attr 
9365   
9366          # Set what to extract. 
9367          err_attr = err_attr_list[0] 
9368   
9369          # Define list with text. 
9370          text_list = [] 
9371   
9372          # Now loop through the data. 
9373          for spin_id in spin_id_list: 
9374              for est_key in est_keys: 
9375                  # Define list to pickup data. 
9376                  r2eff_err_list = [] 
9377   
9378                  for param_key in param_key_list: 
9379                      # Get the value. 
9380                      r2eff_err = my_dic[spin_id][est_key][param_key][err_attr] 
9381   
9382                      # Add to list. 
9383                      r2eff_err_list.append(r2eff_err) 
9384   
9385                  # Sum the list 
9386                  sum_array = sum(array(r2eff_err_list)) 
9387   
9388                  # Join floats to string. 
9389                  r2eff_err_str = " ".join(format(x, "2.3f") for x in r2eff_err_list) 
9390   
9391                  # Define print string. 
9392                  text = "%8s %s sum= %2.3f" % (est_key, r2eff_err_str, sum_array) 
9393                  text_list.append(text) 
9394   
9395   
9396          # Now print. 
9397          filepath = NamedTemporaryFile(delete=False).name 
9398          # Open the files for testing. 
9399          w_file = open(filepath, 'w') 
9400   
9401          print("Printing the estimated R2eff error as function of estimation from Co-variance and number of Monte-Carlo simulations.") 
9402   
9403          for text in text_list: 
9404              # Print. 
9405              print(text) 
9406   
9407              # Write to file. 
9408              w_file.write(text+"\n") 
9409   
9410          # Close files 
9411          w_file.close() 
9412   
9413          print("Filepath is: %s"%filepath) 
9414          print("Start 'gnuplot' and write:") 
9415          print("set term dumb") 
9416          print("plot '%s' using 1:17 title 'R2eff error as function of MC number' w linespoints "%filepath) 
9417   
9418   
9419 -    def verify_r1rho_kjaergaard_missing_r1(self, models=None, result_dir_name=None, r2eff_estimate=None): 
9420          """Verification of test_r1rho_kjaergaard_missing_r1.""" 
9421   
9422          # Check the kex value of residue 52 
9423          #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ds.ref[':52@N'][6]) 
9424   
9425          # Print results for each model. 
9426          print("\n\n################") 
9427          print("Printing results") 
9428          print("################\n") 
9429          for model in models: 
9430              # Skip R2eff model. 
9431              if model == MODEL_R2EFF: 
9432                  continue 
9433   
9434              # Switch to pipe. 
9435              self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
9436              print("\nModel: %s" % (model)) 
9437   
9438              # Loop over the spins. 
9439              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9440                  # Generate spin string. 
9441                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9442   
9443                  # Loop over the parameters. 
9444                  print("Optimised parameters for spin: %s" % (spin_string)) 
9445                  for param in cur_spin.params + ['chi2']: 
9446                      # Get the value. 
9447                      if param in ['r1', 'r2']: 
9448                          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
9449                              # Generate the R20 key. 
9450                              r20_key = generate_r20_key(exp_type=exp_type, frq=frq) 
9451   
9452                              # Get the value. 
9453                              value = getattr(cur_spin, param)[r20_key] 
9454   
9455                              # Print value. 
9456                              print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) 
9457   
9458                              # Compare values. 
9459                              if spin_id == ':52@N': 
9460                                  if param == 'r1': 
9461                                      if model == MODEL_NOREX: 
9462                                          if r2eff_estimate == 'direct': 
9463                                              self.assertAlmostEqual(value, 1.46138805) 
9464                                          elif r2eff_estimate == 'MC2000': 
9465                                              self.assertAlmostEqual(value, 1.46328102) 
9466                                          elif r2eff_estimate == 'chi2_pyt': 
9467                                              self.assertAlmostEqual(value, 1.43820629) 
9468                                      elif model == MODEL_DPL94: 
9469                                          if r2eff_estimate == 'direct': 
9470                                              self.assertAlmostEqual(value, 1.44845742) 
9471                                          elif r2eff_estimate == 'MC2000': 
9472                                              self.assertAlmostEqual(value, 1.45019848) 
9473                                          elif r2eff_estimate == 'chi2_pyt': 
9474                                              self.assertAlmostEqual(value, 1.44666512) 
9475                                      elif model == MODEL_TP02: 
9476                                          if r2eff_estimate == 'direct': 
9477                                              self.assertAlmostEqual(value, 1.54354392) 
9478                                          elif r2eff_estimate == 'MC2000': 
9479                                              self.assertAlmostEqual(value, 1.54352369) 
9480                                          elif r2eff_estimate == 'chi2_pyt': 
9481                                              self.assertAlmostEqual(value, 1.55964020) 
9482                                      elif model == MODEL_TAP03: 
9483                                          if r2eff_estimate == 'direct': 
9484                                              self.assertAlmostEqual(value, 1.54356410) 
9485                                          elif r2eff_estimate == 'MC2000': 
9486                                              self.assertAlmostEqual(value, 1.54354367) 
9487                                          elif r2eff_estimate == 'chi2_pyt': 
9488                                              self.assertAlmostEqual(value, 1.55967157) 
9489                                      elif model == MODEL_MP05: 
9490                                          if r2eff_estimate == 'direct': 
9491                                              self.assertAlmostEqual(value, 1.54356416) 
9492                                          elif r2eff_estimate == 'MC2000': 
9493                                              self.assertAlmostEqual(value, 1.54354372) 
9494                                          elif r2eff_estimate == 'chi2_pyt': 
9495                                              self.assertAlmostEqual(value, 1.55967163) 
9496                                      elif model == MODEL_NS_R1RHO_2SITE: 
9497                                          if r2eff_estimate == 'direct': 
9498                                              self.assertAlmostEqual(value, 1.41359221, 5) 
9499                                          elif r2eff_estimate == 'MC2000': 
9500                                              self.assertAlmostEqual(value, 1.41321968, 5) 
9501                                          elif r2eff_estimate == 'chi2_pyt': 
9502                                              self.assertAlmostEqual(value, 1.36303129, 5) 
9503   
9504                                  elif param == 'r2': 
9505                                      if model == MODEL_NOREX: 
9506                                          if r2eff_estimate == 'direct': 
9507                                              self.assertAlmostEqual(value, 11.48392439) 
9508                                          elif r2eff_estimate == 'MC2000': 
9509                                              self.assertAlmostEqual(value, 11.48040934) 
9510                                          elif r2eff_estimate == 'chi2_pyt': 
9511                                              self.assertAlmostEqual(value, 11.47224488) 
9512                                      elif model == MODEL_DPL94: 
9513                                          if r2eff_estimate == 'direct': 
9514                                              self.assertAlmostEqual(value, 10.15688372, 6) 
9515                                          elif r2eff_estimate == 'MC2000': 
9516                                              self.assertAlmostEqual(value, 10.16304887, 6) 
9517                                          elif r2eff_estimate == 'chi2_pyt': 
9518                                              self.assertAlmostEqual(value, 9.20037797, 6) 
9519                                      elif model == MODEL_TP02: 
9520                                          if r2eff_estimate == 'direct': 
9521                                              self.assertAlmostEqual(value, 9.72654896, 6) 
9522                                          elif r2eff_estimate == 'MC2000': 
9523                                              self.assertAlmostEqual(value, 9.72772726, 6) 
9524                                          elif r2eff_estimate == 'chi2_pyt': 
9525                                              self.assertAlmostEqual(value, 9.53948340, 6) 
9526                                      elif model == MODEL_TAP03: 
9527                                          if r2eff_estimate == 'direct': 
9528                                              self.assertAlmostEqual(value, 9.72641887, 6) 
9529                                          elif r2eff_estimate == 'MC2000': 
9530                                              self.assertAlmostEqual(value, 9.72759374, 6) 
9531                                          elif r2eff_estimate == 'chi2_pyt': 
9532                                              self.assertAlmostEqual(value, 9.53926913, 6) 
9533                                      elif model == MODEL_MP05: 
9534                                          if r2eff_estimate == 'direct': 
9535                                              self.assertAlmostEqual(value, 9.72641723, 6) 
9536                                          elif r2eff_estimate == 'MC2000': 
9537                                              self.assertAlmostEqual(value, 9.72759220, 6) 
9538                                          elif r2eff_estimate == 'chi2_pyt': 
9539                                              self.assertAlmostEqual(value, 9.53926778, 6) 
9540                                      elif model == MODEL_NS_R1RHO_2SITE: 
9541                                          if r2eff_estimate == 'direct': 
9542                                              self.assertAlmostEqual(value, 9.34531535, 5) 
9543                                          elif r2eff_estimate == 'MC2000': 
9544                                              self.assertAlmostEqual(value, 9.34602793, 5) 
9545                                          elif r2eff_estimate == 'chi2_pyt': 
9546                                              self.assertAlmostEqual(value, 9.17631409, 5) 
9547   
9548                      # For all other parameters. 
9549                      else: 
9550                          # Get the value. 
9551                          value = getattr(cur_spin, param) 
9552   
9553                          # Print value. 
9554                          print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) 
9555   
9556                          # Compare values. 
9557                          if spin_id == ':52@N': 
9558                              if param == 'phi_ex': 
9559                                  if model == MODEL_DPL94: 
9560                                      if r2eff_estimate == 'direct': 
9561                                          self.assertAlmostEqual(value, 0.07599563) 
9562                                      elif r2eff_estimate == 'MC2000': 
9563                                          self.assertAlmostEqual(value, 0.07561937) 
9564                                      elif r2eff_estimate == 'chi2_pyt': 
9565                                          self.assertAlmostEqual(value, 0.12946061) 
9566   
9567                              elif param == 'pA': 
9568                                  if model == MODEL_TP02: 
9569                                      if r2eff_estimate == 'direct': 
9570                                          self.assertAlmostEqual(value, 0.88827040) 
9571                                      elif r2eff_estimate == 'MC2000': 
9572                                          self.assertAlmostEqual(value, 0.88807487) 
9573                                      elif r2eff_estimate == 'chi2_pyt': 
9574                                          self.assertAlmostEqual(value, 0.87746233) 
9575                                  elif model == MODEL_TAP03: 
9576                                      if r2eff_estimate == 'direct': 
9577                                          self.assertAlmostEqual(value, 0.88828922) 
9578                                      elif r2eff_estimate == 'MC2000': 
9579                                          self.assertAlmostEqual(value, 0.88809318) 
9580                                      elif r2eff_estimate == 'chi2_pyt': 
9581                                          self.assertAlmostEqual(value, 0.87747558) 
9582                                  elif model == MODEL_MP05: 
9583                                      if r2eff_estimate == 'direct': 
9584                                          self.assertAlmostEqual(value, 0.88828924, 6) 
9585                                      elif r2eff_estimate == 'MC2000': 
9586                                          self.assertAlmostEqual(value, 0.88809321) 
9587                                      elif r2eff_estimate == 'chi2_pyt': 
9588                                          self.assertAlmostEqual(value, 0.87747562) 
9589                                  elif model == MODEL_NS_R1RHO_2SITE: 
9590                                      if r2eff_estimate == 'direct': 
9591                                          self.assertAlmostEqual(value, 0.94504369, 6) 
9592                                      elif r2eff_estimate == 'MC2000': 
9593                                          self.assertAlmostEqual(value, 0.94496541, 6) 
9594                                      elif r2eff_estimate == 'chi2_pyt': 
9595                                          self.assertAlmostEqual(value, 0.92084707, 6) 
9596   
9597                              elif param == 'dw': 
9598                                  if model == MODEL_TP02: 
9599                                      if r2eff_estimate == 'direct': 
9600                                          self.assertAlmostEqual(value, 1.08875840, 6) 
9601                                      elif r2eff_estimate == 'MC2000': 
9602                                          self.assertAlmostEqual(value, 1.08765638, 6) 
9603                                      elif r2eff_estimate == 'chi2_pyt': 
9604                                          self.assertAlmostEqual(value, 1.09753230, 6) 
9605                                  elif model == MODEL_TAP03: 
9606                                      if r2eff_estimate == 'direct': 
9607                                          self.assertAlmostEqual(value, 1.08837238, 6) 
9608                                      elif r2eff_estimate == 'MC2000': 
9609                                          self.assertAlmostEqual(value, 1.08726698, 6) 
9610                                      elif r2eff_estimate == 'chi2_pyt': 
9611                                          self.assertAlmostEqual(value, 1.09708821, 6) 
9612                                  elif model == MODEL_MP05: 
9613                                      if r2eff_estimate == 'direct': 
9614                                          self.assertAlmostEqual(value, 1.08837241, 6) 
9615                                      elif r2eff_estimate == 'MC2000': 
9616                                          self.assertAlmostEqual(value, 1.08726706, 6) 
9617                                      elif r2eff_estimate == 'chi2_pyt': 
9618                                          self.assertAlmostEqual(value, 1.09708832, 6) 
9619                                  elif model == MODEL_NS_R1RHO_2SITE: 
9620                                      if r2eff_estimate == 'direct': 
9621                                          self.assertAlmostEqual(value, 1.56001812, 5) 
9622                                      elif r2eff_estimate == 'MC2000': 
9623                                          self.assertAlmostEqual(value, 1.55833321, 5) 
9624                                      elif r2eff_estimate == 'chi2_pyt': 
9625                                          self.assertAlmostEqual(value, 1.36406712, 5) 
9626   
9627                              elif param == 'kex': 
9628                                  if model == MODEL_DPL94: 
9629                                      if r2eff_estimate == 'direct': 
9630                                          self.assertAlmostEqual(value/1e5, 4460.43711569/1e5, 7) 
9631                                      elif r2eff_estimate == 'MC2000': 
9632                                          self.assertAlmostEqual(value/1e5, 4419.03917195/1e5, 7) 
9633                                      elif r2eff_estimate == 'chi2_pyt': 
9634                                          self.assertAlmostEqual(value/1e5, 6790.22736344/1e5, 7) 
9635                                  elif model == MODEL_TP02: 
9636                                      if r2eff_estimate == 'direct': 
9637                                          self.assertAlmostEqual(value/1e5, 4921.28602757/1e5, 7) 
9638                                      elif r2eff_estimate == 'MC2000': 
9639                                          self.assertAlmostEqual(value/1e5, 4904.70144883/1e5, 7) 
9640                                      elif r2eff_estimate == 'chi2_pyt': 
9641                                          self.assertAlmostEqual(value/1e5, 5146.20306591/1e5, 7) 
9642                                  elif model == MODEL_TAP03: 
9643                                      if r2eff_estimate == 'direct': 
9644                                          self.assertAlmostEqual(value/1e5, 4926.42963491/1e5, 7) 
9645                                      elif r2eff_estimate == 'MC2000': 
9646                                          self.assertAlmostEqual(value/1e5, 4909.86877150/1e5, 7) 
9647                                      elif r2eff_estimate == 'chi2_pyt': 
9648                                          self.assertAlmostEqual(value/1e5, 5152.51105814/1e5, 7) 
9649                                  elif model == MODEL_MP05: 
9650                                      if r2eff_estimate == 'direct': 
9651                                          self.assertAlmostEqual(value/1e5, 4926.44236315/1e5, 7) 
9652                                      elif r2eff_estimate == 'MC2000': 
9653                                          self.assertAlmostEqual(value/1e5, 4909.88110195/1e5, 7) 
9654                                      elif r2eff_estimate == 'chi2_pyt': 
9655                                          self.assertAlmostEqual(value/1e5, 5152.52097111/1e5, 7) 
9656                                  elif model == MODEL_NS_R1RHO_2SITE: 
9657                                      if r2eff_estimate == 'direct': 
9658                                          self.assertAlmostEqual(value/1e5, 5628.66061488/1e5, 6) 
9659                                      elif r2eff_estimate == 'MC2000': 
9660                                          self.assertAlmostEqual(value/1e5, 5610.20221435/1e5, 6) 
9661                                      elif r2eff_estimate == 'chi2_pyt': 
9662                                          self.assertAlmostEqual(value/1e5, 5643.34067090/1e5, 6) 
9663   
9664                              elif param == 'chi2': 
9665                                  if model == MODEL_NOREX: 
9666                                      if r2eff_estimate == 'direct': 
9667                                          self.assertAlmostEqual(value, 848.42016907, 5) 
9668                                      elif r2eff_estimate == 'MC2000': 
9669                                          self.assertAlmostEqual(value, 3363.95829122, 5) 
9670                                      elif r2eff_estimate == 'chi2_pyt': 
9671                                          self.assertAlmostEqual(value, 5976.49946726, 5) 
9672                                  elif model == MODEL_DPL94: 
9673                                      if r2eff_estimate == 'direct': 
9674                                          self.assertAlmostEqual(value, 179.47041241) 
9675                                      elif r2eff_estimate == 'MC2000': 
9676                                          self.assertAlmostEqual(value, 710.24767560) 
9677                                      elif r2eff_estimate == 'chi2_pyt': 
9678                                          self.assertAlmostEqual(value, 612.72616697, 5) 
9679                                  elif model == MODEL_TP02: 
9680                                      if r2eff_estimate == 'direct': 
9681                                          self.assertAlmostEqual(value, 29.33882530, 6) 
9682                                      elif r2eff_estimate == 'MC2000': 
9683                                          self.assertAlmostEqual(value, 114.47142772, 6) 
9684                                      elif r2eff_estimate == 'chi2_pyt': 
9685                                          self.assertAlmostEqual(value, 250.50838162, 5) 
9686                                  elif model == MODEL_TAP03: 
9687                                      if r2eff_estimate == 'direct': 
9688                                          self.assertAlmostEqual(value, 29.29050673, 6) 
9689                                      elif r2eff_estimate == 'MC2000': 
9690                                          self.assertAlmostEqual(value, 114.27987534) 
9691                                      elif r2eff_estimate == 'chi2_pyt': 
9692                                          self.assertAlmostEqual(value, 250.04050719, 5) 
9693                                  elif model == MODEL_MP05: 
9694                                      if r2eff_estimate == 'direct': 
9695                                          self.assertAlmostEqual(value, 29.29054301, 6) 
9696                                      elif r2eff_estimate == 'MC2000': 
9697                                          self.assertAlmostEqual(value, 114.28002272) 
9698                                      elif r2eff_estimate == 'chi2_pyt': 
9699                                          self.assertAlmostEqual(value, 250.04077478, 5) 
9700                                  elif model == MODEL_NS_R1RHO_2SITE: 
9701                                      if r2eff_estimate == 'direct': 
9702                                          self.assertAlmostEqual(value, 34.44010543, 6) 
9703                                      elif r2eff_estimate == 'MC2000': 
9704                                          self.assertAlmostEqual(value, 134.14368365) 
9705                                      elif r2eff_estimate == 'chi2_pyt': 
9706                                          self.assertAlmostEqual(value, 278.55121388, 5) 
9707   
9708   
9709          # Print the final pipe. 
9710          model = 'final' 
9711          self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
9712          print("\nFinal pipe") 
9713   
9714          # Loop over the spins. 
9715          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9716              # Generate spin string. 
9717              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9718   
9719              # Loop over the parameters. 
9720              print("Optimised model for spin: %s" % (spin_string)) 
9721              param = 'model' 
9722   
9723              # Get the value. 
9724              value = getattr(cur_spin, param) 
9725              print("%-10s %-6s %-6s %6s" % ("Parameter:", param, "Value:", value)) 
9726   
9727   
9728          ### Now check some of the written out files. 
9729          file_names = ['r1rho_prime', 'r1'] 
9730   
9731          for file_name_i in file_names: 
9732   
9733              # Make the file name. 
9734              file_name = "%s.out" % file_name_i 
9735   
9736              # Get the file path. 
9737              file_path = get_file_path(file_name, result_dir_name + sep + model) 
9738   
9739              # Test the file exists. 
9740              print("Testing file access to: %s"%file_path) 
9741              self.assert_(access(file_path, F_OK)) 
9742   
9743              # Now open, and compare content, line by line. 
9744              file_prod = open(file_path) 
9745              lines_prod = file_prod.readlines() 
9746              file_prod.close() 
9747   
9748              # Loop over the lines. 
9749              for i, line in enumerate(lines_prod): 
9750                  # Make the string test 
9751                  line_split = line.split() 
9752   
9753                  # Continue for comment lines. 
9754                  if line_split[0] == "#": 
9755                      print(line), 
9756                      continue 
9757   
9758                  # Assign the split of the line. 
9759                  mol_name, res_num, res_name, spin_num, spin_name, val, sd_error = line_split 
9760                  print(mol_name, res_num, res_name, spin_num, spin_name, val, sd_error) 
9761   
9762                  if res_num == '52': 
9763                      # Assert that the value is not None. 
9764                      self.assertNotEqual(val, 'None') 
9765